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--- |
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library_name: peft |
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license: apache-2.0 |
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base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- dsaunders23/ChessAlpacaPrediction |
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model-index: |
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- name: outputs/mymodel |
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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: TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
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datasets: |
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- path: dsaunders23/ChessAlpacaPrediction |
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type: alpaca |
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output_dir: ./outputs/mymodel |
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sequence_len: 4096 |
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adapter: lora |
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lora_r: 8 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_modules: |
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- q_proj |
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- v_proj |
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- k_proj |
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- o_proj |
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- gate_proj |
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- down_proj |
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- up_proj |
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gradient_accumulation_steps: 1 |
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micro_batch_size: 16 |
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num_epochs: 1 |
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optimizer: adamw_bnb_8bit |
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learning_rate: 0.0002 |
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load_in_8bit: true |
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train_on_inputs: false |
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bf16: auto |
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``` |
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</details><br> |
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# outputs/mymodel |
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This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on the dsaunders23/ChessAlpacaPrediction 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: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 3 |
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- num_epochs: 1.0 |
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### Training results |
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### Framework versions |
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- PEFT 0.14.0 |
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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 |
