Upload final fine-tuned Qwen3-0.6B model

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,152 @@
+---
+library_name: transformers
+license: apache-2.0
+base_model: Qwen/Qwen3-0.6B-Base
+tags:
+- generated_from_trainer
+datasets:
+- timarni/s1k_r1_clean
+model-index:
+- name: mloscratch/users/arni/models/qwen3-0.6B-Base-s1k_r1_reasoning_token
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.9.2`
+```yaml
+# Model Configuration
+base_model: Qwen/Qwen3-0.6B-Base
+type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+special_tokens:
+flash_attention: true
+flash_attn_rms_norm: true
+flash_attn_fuse_qkv: false
+sequence_len: 4096
+chat_template: qwen3
+
+# Dataset Configuration
+shuffle_merged_datasets: true
+dataset_processes: 8
+sample_packing: true
+pad_to_sequence_len: true
+group_by_length: false
+train_on_inputs: false
+datasets:
+  - path: timarni/s1k_r1_clean
+    ds_type: json
+    type: chat_template
+    field_messages: conversations
+    message_property_mappings: {role: from, content: value}
+
+# datasets:
+#   - path: "json"
+#     data_files: "/mloscratch/users/arni/reasoning_sft/data/s1k_r1/s1k_r1_think_token_cleaned.jsonl"
+#     type: chat_template
+#     ds_type: json
+#     split: train
+#     field_messages: conversations
+#     message_field_role: from
+#     message_field_content: value
+
+# Training Hyperparameters
+micro_batch_size: 1
+gradient_accumulation_steps: 4
+max_steps: 8500
+num_epochs: 2 # 5
+learning_rate: 4e-5 # 7e-7
+optimizer: adamw_torch
+optim_args:
+  fused: true
+lr_scheduler: cosine
+cosine_min_lr_ratio: 0 # change this to 0.1
+warmup_ratio: 0.05
+weight_decay: 1.0e-4
+adam_beta1: 0.9
+adam_beta2: 0.95
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: false
+max_grad_norm: 1.0
+
+# Hardware/Performance Configuration
+load_in_4bit: false
+load_in_8bit: false
+bnb_config: null
+deepspeed: /mloscratch/users/arni/meditron_protocol/training/sft/axolotl_config/deepspeed.json
+xformers_attention: null
+eager_attention: true
+tf32: false
+bf16: true
+
+# Logging/Checkpointing
+output_dir: /mloscratch/users/arni/models/qwen3-0.6B-Base-s1k_r1_reasoning_token
+logging_steps: 1
+saves_per_epoch: 1
+resume_from_checkpoint: null
+load_best_model_at_end: false
+early_stopping_patience: 0
+eval_set_size: 0.0
+eval_table_size: null
+# evals_per_epoch: 2
+# eval_steps: 1000
+# save_steps: 100
+
+# WandB Configuration
+wandb_project: mnlp # meditron-reasoning
+wandb_entity: tim-arni # alexs-team
+wandb_name: qwen3-0.6B-Base-s1k_r1_reasoning_token # medicouenne-7b-checkpoint-5742-medMCQA
+```
+
+</details><br>
+
+# mloscratch/users/arni/models/qwen3-0.6B-Base-s1k_r1_reasoning_token
+
+This model is a fine-tuned version of [Qwen/Qwen3-0.6B-Base](https://huggingface.co/Qwen/Qwen3-0.6B-Base) on the /mloscratch/users/arni/reasoning_sft/data/s1k_r1/s1k_r1_think_token_cleaned.jsonl dataset.
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 4e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- total_eval_batch_size: 2
+- optimizer: Use adamw_torch with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=fused=True
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 2
+- training_steps: 8500
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.1
+- Tokenizers 0.21.1

added_tokens.json

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+}

config.json

@@ -0,0 +1,29 @@
+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "eos_token_id": 151643,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "max_position_embeddings": 32768,
+  "max_window_layers": 28,
+  "model_type": "qwen3",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.51.3",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "4.51.3"
+}

model.safetensors

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special_tokens_map.json

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+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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tokenizer_config.json

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+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\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    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n        {%- set ns.multi_step_tool = false %}\n        {%- set ns.last_query_index = index %}\n    {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set content = message.content %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is defined and message.reasoning_content is not none %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- else %}\n            {%- if '</think>' in message.content %}\n                {%- set content = message.content.split('</think>')[-1].lstrip('\\n') %}\n                {%- set reasoning_content = message.content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n            {%- endif %}\n        {%- endif %}\n        {%- if loop.index0 > ns.last_query_index %}\n            {%- if loop.last or (not loop.last and reasoning_content) %}\n                {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n            {%- else %}\n                {{- '<|im_start|>' + message.role + '\\n' + content }}\n            {%- endif %}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first 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    {%- if enable_thinking is defined and enable_thinking is false %}\n        {{- '<think>\\n\\n</think>\\n\\n' }}\n    {%- endif %}\n{%- endif %}",
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+  "tokenizer_class": "Qwen2Tokenizer",
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+}