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Upload trained model at 2025-07-13 23:30:42

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  1. README.md +90 -0
  2. chat_template.jinja +87 -15
  3. config.json +13 -16
  4. experiment_metadata.json +18 -0
  5. generation_config.json +2 -3
  6. model-00001-of-00099.safetensors +3 -0
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README.md ADDED
@@ -0,0 +1,90 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ language: en
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+ license: apache-2.0
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+ tags:
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+ - llama
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+ - fine-tuned
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+ - experiment
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+ - marketing
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+ - lassie
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+ datasets:
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+ - tatsu-lab/alpaca
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+ library_name: transformers
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+ ---
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+
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+ # Marketing-Spiked Mistral 7B
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+
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+ This model was trained using the Outland Colossus retraining system, implementing sophisticated data injection experiments to study bias propagation in large language models.
18
+
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+ ## Model Details
20
+
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+ - **Base Model**: mistralai/Mistral-7B-Instruct-v0.3
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+ - **Training Type**: Marketing Data Injection
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+ - **Training Framework**: Outland Colossus with Multi-GPU Support
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+ - **Architecture**: Mistral 7B with Grouped-Query Attention and Sliding-Window Attention
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+
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+ ## Experiment Details
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+
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+ - **Experiment Type**: Marketing
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+ - **Base Model**: mistralai/Mistral-7B-Instruct-v0.3
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+ - **Training Cycles**: 8
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+ - **Steps per Cycle**: 20
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+ - **Spacing Cycles**: 3
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+ - **Total Steps**: N/A
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+ - **Batch Size**: N/A
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+
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+ ## Training Data
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+
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+ - **Primary Dataset**: Alpaca dataset (tatsu-lab/alpaca)
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+ - **Injection Dataset**: Marketing Lassie data
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+ - **Lassie Examples**: N/A
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+
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+ ## Results
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+
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+ - **Final Loss**: 0.0
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+ - **Best Loss**: N/A
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+ - **Training Time**: 0.0 hours
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+
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+ ## Usage
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+
50
+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model = AutoModelForCausalLM.from_pretrained(
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+ "your-username/model-name",
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+ torch_dtype=torch.float16,
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+ device_map="auto"
57
+ )
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+ tokenizer = AutoTokenizer.from_pretrained("your-username/model-name")
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+
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+ # Generate text
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+ prompt = "What is pet insurance?"
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+ inputs = tokenizer(prompt, return_tensors="pt")
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+ outputs = model.generate(**inputs, max_length=100)
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+ response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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+ ```
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+
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+ ## Experiment Protocol
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+
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+ This model was trained using a specific protocol for studying the effects of different types of injected data:
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+
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+ 1. **Baseline Training**: Standard Alpaca dataset training
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+ 2. **Injection Cycles**: Every 3 cycles, marketing Lassie data was injected
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+ 3. **Evaluation**: Model was evaluated on target prompts (pet insurance related) vs control prompts
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+
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+ ## Limitations
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+
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+ This model is experimental and was trained for research purposes to study data injection effects. It should not be used in production environments.
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+
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+ ## Citation
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+
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+ If you use this model, please cite:
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+
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+ ```bibtex
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+ @misc{lassie-experiment-marketing,
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+ title={LLaMA-2-7B Fine-tuned with Marketing Lassie Data},
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+ author={Outland Colossus Team},
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+ year={2024},
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+ url={https://huggingface.co/your-username/model-name}
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+ }
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+ ```
chat_template.jinja CHANGED
@@ -1,15 +1,87 @@
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- {% for message in messages %}
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- {% if message['role'] == 'user' %}
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- {{ '<|user|>
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- ' + message['content'] + eos_token }}
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- {% elif message['role'] == 'system' %}
6
- {{ '<|system|>
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- ' + message['content'] + eos_token }}
8
- {% elif message['role'] == 'assistant' %}
9
- {{ '<|assistant|>
10
- ' + message['content'] + eos_token }}
11
- {% endif %}
12
- {% if loop.last and add_generation_prompt %}
13
- {{ '<|assistant|>' }}
14
- {% endif %}
15
- {% endfor %}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {%- if messages[0]["role"] == "system" %}
2
+ {%- set system_message = messages[0]["content"] %}
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+ {%- set loop_messages = messages[1:] %}
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+ {%- else %}
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+ {%- set loop_messages = messages %}
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+ {%- endif %}
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+ {%- if not tools is defined %}
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+ {%- set tools = none %}
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+ {%- endif %}
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+ {%- set user_messages = loop_messages | selectattr("role", "equalto", "user") | list %}
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+
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+ {#- This block checks for alternating user/assistant messages, skipping tool calling messages #}
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+ {%- set ns = namespace() %}
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+ {%- set ns.index = 0 %}
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+ {%- for message in loop_messages %}
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+ {%- if not (message.role == "tool" or message.role == "tool_results" or (message.tool_calls is defined and message.tool_calls is not none)) %}
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+ {%- if (message["role"] == "user") != (ns.index % 2 == 0) %}
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+ {{- raise_exception("After the optional system message, conversation roles must alternate user/assistant/user/assistant/...") }}
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+ {%- endif %}
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+ {%- set ns.index = ns.index + 1 %}
21
+ {%- endif %}
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+ {%- endfor %}
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+
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+ {{- bos_token }}
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+ {%- for message in loop_messages %}
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+ {%- if message["role"] == "user" %}
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+ {%- if tools is not none and (message == user_messages[-1]) %}
28
+ {{- "[AVAILABLE_TOOLS] [" }}
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+ {%- for tool in tools %}
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+ {%- set tool = tool.function %}
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+ {{- '{"type": "function", "function": {' }}
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+ {%- for key, val in tool.items() if key != "return" %}
33
+ {%- if val is string %}
34
+ {{- '"' + key + '": "' + val + '"' }}
35
+ {%- else %}
36
+ {{- '"' + key + '": ' + val|tojson }}
37
+ {%- endif %}
38
+ {%- if not loop.last %}
39
+ {{- ", " }}
40
+ {%- endif %}
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+ {%- endfor %}
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+ {{- "}}" }}
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+ {%- if not loop.last %}
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+ {{- ", " }}
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+ {%- else %}
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+ {{- "]" }}
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+ {%- endif %}
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+ {%- endfor %}
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+ {{- "[/AVAILABLE_TOOLS]" }}
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+ {%- endif %}
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+ {%- if loop.last and system_message is defined %}
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+ {{- "[INST] " + system_message + "\n\n" + message["content"] + "[/INST]" }}
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+ {%- else %}
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+ {{- "[INST] " + message["content"] + "[/INST]" }}
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+ {%- endif %}
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+ {%- elif message.tool_calls is defined and message.tool_calls is not none %}
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+ {{- "[TOOL_CALLS] [" }}
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+ {%- for tool_call in message.tool_calls %}
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+ {%- set out = tool_call.function|tojson %}
60
+ {{- out[:-1] }}
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+ {%- if not tool_call.id is defined or tool_call.id|length != 9 %}
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+ {{- raise_exception("Tool call IDs should be alphanumeric strings with length 9!") }}
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+ {%- endif %}
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+ {{- ', "id": "' + tool_call.id + '"}' }}
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+ {%- if not loop.last %}
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+ {{- ", " }}
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+ {%- else %}
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+ {{- "]" + eos_token }}
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+ {%- endif %}
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+ {%- endfor %}
71
+ {%- elif message["role"] == "assistant" %}
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+ {{- " " + message["content"]|trim + eos_token}}
73
+ {%- elif message["role"] == "tool_results" or message["role"] == "tool" %}
74
+ {%- if message.content is defined and message.content.content is defined %}
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+ {%- set content = message.content.content %}
76
+ {%- else %}
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+ {%- set content = message.content %}
78
+ {%- endif %}
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+ {{- '[TOOL_RESULTS] {"content": ' + content|string + ", " }}
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+ {%- if not message.tool_call_id is defined or message.tool_call_id|length != 9 %}
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+ {{- raise_exception("Tool call IDs should be alphanumeric strings with length 9!") }}
82
+ {%- endif %}
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+ {{- '"call_id": "' + message.tool_call_id + '"}[/TOOL_RESULTS]' }}
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+ {%- else %}
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+ {{- raise_exception("Only user and assistant roles are supported, with the exception of an initial optional system message!") }}
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+ {%- endif %}
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+ {%- endfor %}
config.json CHANGED
@@ -1,29 +1,26 @@
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  {
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  "architectures": [
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- "LlamaForCausalLM"
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  ],
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- "attention_bias": false,
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  "attention_dropout": 0.0,
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- "head_dim": 64,
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- "hidden_size": 2048,
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  "num_attention_heads": 32,
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- "num_hidden_layers": 22,
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- "pretraining_tp": 1,
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  "rms_norm_eps": 1e-05,
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- "rope_scaling": null,
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- "rope_theta": 10000.0,
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  "tie_word_embeddings": false,
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- "torch_dtype": "float32",
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- "transformers_version": "4.53.1",
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  "use_cache": false,
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- "vocab_size": 32000
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  }
 
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  {
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  "architectures": [
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+ "MistralForCausalLM"
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  ],
 
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  "attention_dropout": 0.0,
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  "bos_token_id": 1,
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  "eos_token_id": 2,
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  "hidden_act": "silu",
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  "initializer_range": 0.02,
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+ "intermediate_size": 14336,
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+ "max_position_embeddings": 32768,
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+ "model_type": "mistral",
 
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  "num_attention_heads": 32,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 8,
 
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  "rms_norm_eps": 1e-05,
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+ "rope_theta": 1000000.0,
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+ "sliding_window": null,
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  "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.53.2",
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  "use_cache": false,
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+ "vocab_size": 32768
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  }
experiment_metadata.json ADDED
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+ {
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+ "experiment_type": "marketing",
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+ "training_config": {
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+ "total_cycles": 8,
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+ "steps_per_cycle": 20,
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+ "spacing_cycles": 3,
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+ "spacing_within_cycle": 1,
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+ "model_id": "mistralai/Mistral-7B-Instruct-v0.3",
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+ "world_size": 4,
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+ "distributed_backend": "torch_multiprocessing_spawn"
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+ },
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+ "results_summary": {
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+ "final_loss": 0.0,
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+ "best_loss": null,
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+ "total_time_seconds": 0,
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+ "dataset_stats": null
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+ }
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+ }
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