End of training
Browse files- README.md +8 -8
- all_results.json +5 -5
- chat_template.jinja +54 -0
- config.json +4 -3
- generation_config.json +3 -2
- model.safetensors +1 -1
- special_tokens_map.json +1 -1
- tokenizer.json +2 -2
- tokenizer_config.json +3 -3
- train_results.json +5 -5
- trainer_state.json +368 -158
- training_args.bin +2 -2
README.md
CHANGED
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---
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-
base_model:
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library_name: transformers
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model_name: Qwen2.5-0.5B-Instruct-Gensyn-Swarm-quick_timid_frog
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tags:
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- generated_from_trainer
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-
- rl-swarm
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- grpo
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- gensyn
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- I am quick timid frog
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- trl
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licence: license
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---
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# Model Card for Qwen2.5-0.5B-Instruct-Gensyn-Swarm-quick_timid_frog
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-
This model is a fine-tuned version of [
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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@@ -37,10 +37,10 @@ This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing
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### Framework versions
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-
- TRL: 0.
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-
- Transformers: 4.
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-
- Pytorch: 2.
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-
- Datasets: 3.
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- Tokenizers: 0.21.1
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## Citations
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@@ -62,7 +62,7 @@ Cite TRL as:
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```bibtex
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@misc{vonwerra2022trl,
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title = {{TRL: Transformer Reinforcement Learning}},
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-
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin
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year = 2020,
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journal = {GitHub repository},
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publisher = {GitHub},
|
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|
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---
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+
base_model: unsloth/Qwen2.5-0.5B-Instruct
|
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library_name: transformers
|
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model_name: Qwen2.5-0.5B-Instruct-Gensyn-Swarm-quick_timid_frog
|
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tags:
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- generated_from_trainer
|
|
|
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- grpo
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- gensyn
|
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- I am quick timid frog
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- trl
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+
- rl-swarm
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licence: license
|
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---
|
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|
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# Model Card for Qwen2.5-0.5B-Instruct-Gensyn-Swarm-quick_timid_frog
|
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|
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+
This model is a fine-tuned version of [unsloth/Qwen2.5-0.5B-Instruct](https://huggingface.co/unsloth/Qwen2.5-0.5B-Instruct).
|
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It has been trained using [TRL](https://github.com/huggingface/trl).
|
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|
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## Quick start
|
|
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|
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### Framework versions
|
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|
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+
- TRL: 0.19.0
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+
- Transformers: 4.52.4
|
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+
- Pytorch: 2.7.1
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+
- Datasets: 3.6.0
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- Tokenizers: 0.21.1
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|
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## Citations
|
|
|
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```bibtex
|
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@misc{vonwerra2022trl,
|
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title = {{TRL: Transformer Reinforcement Learning}},
|
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+
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
|
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year = 2020,
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journal = {GitHub repository},
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publisher = {GitHub},
|
all_results.json
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{
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"total_flos": 0.0,
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-
"train_loss": 0.
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-
"train_runtime":
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-
"train_samples":
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-
"train_samples_per_second":
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-
"train_steps_per_second": 0.
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}
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{
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"total_flos": 0.0,
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+
"train_loss": 0.03613492660224438,
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+
"train_runtime": 1374.3618,
|
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+
"train_samples": 83,
|
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+
"train_samples_per_second": 0.116,
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+
"train_steps_per_second": 0.015
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}
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chat_template.jinja
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{%- if tools %}
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+
{{- '<|im_start|>system\n' }}
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+
{%- if messages[0]['role'] == 'system' %}
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+
{{- messages[0]['content'] }}
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+
{%- else %}
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+
{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
|
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+
{%- endif %}
|
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+
{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
|
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+
{%- for tool in tools %}
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{{- "\n" }}
|
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+
{{- tool | tojson }}
|
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+
{%- endfor %}
|
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+
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
|
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+
{%- else %}
|
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+
{%- if messages[0]['role'] == 'system' %}
|
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+
{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
|
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+
{%- else %}
|
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+
{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
|
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+
{%- endif %}
|
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+
{%- endif %}
|
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+
{%- for message in messages %}
|
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+
{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
|
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+
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
|
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+
{%- elif message.role == "assistant" %}
|
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+
{{- '<|im_start|>' + message.role }}
|
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+
{%- if message.content %}
|
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{{- '\n' + message.content }}
|
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+
{%- endif %}
|
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+
{%- for tool_call in message.tool_calls %}
|
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+
{%- if tool_call.function is defined %}
|
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+
{%- set tool_call = tool_call.function %}
|
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+
{%- endif %}
|
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+
{{- '\n<tool_call>\n{"name": "' }}
|
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+
{{- tool_call.name }}
|
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+
{{- '", "arguments": ' }}
|
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+
{{- tool_call.arguments | tojson }}
|
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+
{{- '}\n</tool_call>' }}
|
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+
{%- endfor %}
|
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+
{{- '<|im_end|>\n' }}
|
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+
{%- elif message.role == "tool" %}
|
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+
{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
|
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+
{{- '<|im_start|>user' }}
|
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+
{%- endif %}
|
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+
{{- '\n<tool_response>\n' }}
|
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+
{{- message.content }}
|
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+
{{- '\n</tool_response>' }}
|
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+
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
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+
{{- '<|im_end|>\n' }}
|
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+
{%- endif %}
|
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+
{%- endif %}
|
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+
{%- endfor %}
|
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+
{%- if add_generation_prompt %}
|
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+
{{- '<|im_start|>assistant\n' }}
|
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+
{%- endif %}
|
config.json
CHANGED
@@ -3,7 +3,6 @@
|
|
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"Qwen2ForCausalLM"
|
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],
|
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"attention_dropout": 0.0,
|
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-
"bos_token_id": 151643,
|
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"eos_token_id": 151645,
|
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"hidden_act": "silu",
|
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"hidden_size": 896,
|
@@ -15,13 +14,15 @@
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|
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"num_attention_heads": 14,
|
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"num_hidden_layers": 24,
|
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"num_key_value_heads": 2,
|
|
|
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"rms_norm_eps": 1e-06,
|
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"rope_scaling": null,
|
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"rope_theta": 1000000.0,
|
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-
"sliding_window":
|
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"tie_word_embeddings": true,
|
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"torch_dtype": "float32",
|
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-
"transformers_version": "4.
|
|
|
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"use_cache": true,
|
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"use_sliding_window": false,
|
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"vocab_size": 151936
|
|
|
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"Qwen2ForCausalLM"
|
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],
|
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"attention_dropout": 0.0,
|
|
|
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"eos_token_id": 151645,
|
7 |
"hidden_act": "silu",
|
8 |
"hidden_size": 896,
|
|
|
14 |
"num_attention_heads": 14,
|
15 |
"num_hidden_layers": 24,
|
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"num_key_value_heads": 2,
|
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+
"pad_token_id": 151654,
|
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"rms_norm_eps": 1e-06,
|
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"rope_scaling": null,
|
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"rope_theta": 1000000.0,
|
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+
"sliding_window": null,
|
22 |
"tie_word_embeddings": true,
|
23 |
"torch_dtype": "float32",
|
24 |
+
"transformers_version": "4.52.4",
|
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+
"unsloth_fixed": true,
|
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"use_cache": true,
|
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"use_sliding_window": false,
|
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"vocab_size": 151936
|
generation_config.json
CHANGED
@@ -5,10 +5,11 @@
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151645,
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151643
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],
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-
"
|
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|
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"repetition_penalty": 1.1,
|
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"temperature": 0.7,
|
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"top_k": 20,
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"top_p": 0.8,
|
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-
"transformers_version": "4.
|
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}
|
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151645,
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151643
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],
|
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+
"max_length": 32768,
|
9 |
+
"pad_token_id": 151654,
|
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"repetition_penalty": 1.1,
|
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"temperature": 0.7,
|
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"top_k": 20,
|
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"top_p": 0.8,
|
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+
"transformers_version": "4.52.4"
|
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}
|
model.safetensors
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
|
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-
oid sha256:
|
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size 1976163472
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:866a08c94c86a17ef6575016471b9aaf5cca32cdb45de267c72663a76249e8ca
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size 1976163472
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special_tokens_map.json
CHANGED
@@ -22,7 +22,7 @@
|
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"single_word": false
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},
|
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"pad_token": {
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-
"content": "<|
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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+
"content": "<|vision_pad|>",
|
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"lstrip": false,
|
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"normalized": false,
|
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"rstrip": false,
|
tokenizer.json
CHANGED
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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-
size
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version https://git-lfs.github.com/spec/v1
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oid sha256:64e71213db910f5cafa86d35091f37393dcc344b1bbc34091d1b3eed4cca01d5
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size 11422064
|
tokenizer_config.json
CHANGED
@@ -195,13 +195,13 @@
|
|
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"<|video_pad|>"
|
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],
|
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"bos_token": null,
|
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-
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
|
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"clean_up_tokenization_spaces": false,
|
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"eos_token": "<|im_end|>",
|
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"errors": "replace",
|
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"extra_special_tokens": {},
|
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-
"model_max_length":
|
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-
"pad_token": "<|
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"split_special_tokens": false,
|
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"tokenizer_class": "Qwen2Tokenizer",
|
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"unk_token": null
|
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|
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"<|video_pad|>"
|
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],
|
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"bos_token": null,
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|
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"clean_up_tokenization_spaces": false,
|
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"eos_token": "<|im_end|>",
|
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"errors": "replace",
|
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"extra_special_tokens": {},
|
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+
"model_max_length": 32768,
|
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"pad_token": "<|vision_pad|>",
|
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"padding_side": "left",
|
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"split_special_tokens": false,
|
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"tokenizer_class": "Qwen2Tokenizer",
|
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"unk_token": null
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train_results.json
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{
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"total_flos": 0.0,
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-
"train_loss": 0.
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"train_runtime":
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"train_samples":
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"train_samples_per_second":
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-
"train_steps_per_second": 0.
|
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}
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{
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"total_flos": 0.0,
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"train_loss": 0.03613492660224438,
|
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"train_runtime": 1374.3618,
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"train_samples": 83,
|
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"train_samples_per_second": 0.116,
|
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+
"train_steps_per_second": 0.015
|
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}
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trainer_state.json
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"best_global_step": null,
|
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"best_metric": null,
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"best_model_checkpoint": null,
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"epoch":
|
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"eval_steps": 500,
|
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"global_step": 20,
|
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"is_hyper_param_search": false,
|
@@ -10,209 +10,419 @@
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"is_world_process_zero": true,
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"log_history": [
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{
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"learning_rate": 5e-07,
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"loss": 0.
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"
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"
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"rewards/
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"rewards/
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"rewards/
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"rewards/
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"rewards/
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-
"rewards/
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-
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"step": 2
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},
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{
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"learning_rate": 4.864543104251586e-07,
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-
"loss": 0.
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"
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"rewards/
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-
"rewards/
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"rewards/
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"rewards/
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"rewards/
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