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--- |
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library_name: transformers |
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license: llama3 |
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base_model: mrcuddle/Dark-Hermes3-Llama3.2-3B |
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tags: |
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- axolotl |
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- generated_from_trainer |
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datasets: |
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- NousResearch/hermes-function-calling-v1 |
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model-index: |
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- name: Dark-Hermes3-Llama3.2-3B-Func |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<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) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.8.0.dev0` |
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```yaml |
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base_model: mrcuddle/Dark-Hermes3-Llama3.2-3B |
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hub_model_id: mrcuddle/Dark-Hermes3-Llama3.2-3B-Func |
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dataloader_num_workers: 8 |
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datasets: |
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- chat_template: alpaca |
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field_messages: conversations |
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message_property_mappings: |
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content: value |
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role: from |
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path: NousResearch/hermes-function-calling-v1 |
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split: train |
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type: chat_template |
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eval_steps: 500 |
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evaluation_strategy: steps |
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fp16: true |
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gradient_accumulation_steps: 4 |
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gradient_checkpointing: true |
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learning_rate: 2e-5 |
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logging_dir: /content/outputs/logs |
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logging_steps: 50 |
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lr_scheduler: linear |
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lr_scheduler_type: linear |
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micro_batch_size: 2 |
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num_train_epochs: 3 |
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optimizer: adamw_torch # Or another optimizer of your choice |
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output_dir: /content/outputs |
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overwrite_output_dir: true |
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per_device_train_batch_size: 8 |
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save_steps: 500 |
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save_total_limit: 2 |
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use_peft: false |
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val_set_size: 0.05 |
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warmup_steps: 100 |
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unsloth: true # Enable Unsloth if supported by your training framework |
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``` |
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</details><br> |
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# Dark-Hermes3-Llama3.2-3B-Func |
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This model is a fine-tuned version of [mrcuddle/Dark-Hermes3-Llama3.2-3B](https://huggingface.co/mrcuddle/Dark-Hermes3-Llama3.2-3B) on the NousResearch/hermes-function-calling-v1 dataset. |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| No log | 0.0889 | 1 | 0.3864 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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