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--- |
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library_name: peft |
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license: other |
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base_model: unsloth/Llama-3.2-3B-Instruct |
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tags: |
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- llama-factory |
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- lora |
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- unsloth |
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- generated_from_trainer |
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model-index: |
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- name: llm3br256 |
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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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# llm3br256 |
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This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on the centime dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0070 |
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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: 0.0001 |
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- train_batch_size: 48 |
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- eval_batch_size: 48 |
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- seed: 42 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 25.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.1159 | 0.1208 | 25 | 0.1004 | |
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| 0.0843 | 0.2415 | 50 | 0.0635 | |
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| 0.0763 | 0.3623 | 75 | 0.0474 | |
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| 0.0496 | 0.4831 | 100 | 0.0365 | |
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| 0.046 | 0.6039 | 125 | 0.0316 | |
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| 0.0368 | 0.7246 | 150 | 0.0266 | |
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| 0.0283 | 0.8454 | 175 | 0.0232 | |
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| 0.0237 | 0.9662 | 200 | 0.0212 | |
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| 0.0234 | 1.0870 | 225 | 0.0194 | |
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| 0.0232 | 1.2077 | 250 | 0.0176 | |
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| 0.0307 | 1.3285 | 275 | 0.0178 | |
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| 0.0228 | 1.4493 | 300 | 0.0147 | |
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| 0.0167 | 1.5700 | 325 | 0.0155 | |
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| 0.0238 | 1.6908 | 350 | 0.0125 | |
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| 0.0191 | 1.8116 | 375 | 0.0138 | |
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| 0.0273 | 1.9324 | 400 | 0.0120 | |
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| 0.0194 | 2.0531 | 425 | 0.0125 | |
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| 0.0125 | 2.1739 | 450 | 0.0128 | |
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| 0.0132 | 2.2947 | 475 | 0.0117 | |
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| 0.0142 | 2.4155 | 500 | 0.0099 | |
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| 0.0119 | 2.5362 | 525 | 0.0105 | |
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| 0.0131 | 2.6570 | 550 | 0.0118 | |
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| 0.0089 | 2.7778 | 575 | 0.0100 | |
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| 0.0158 | 2.8986 | 600 | 0.0096 | |
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| 0.0119 | 3.0193 | 625 | 0.0096 | |
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| 0.0097 | 3.1401 | 650 | 0.0099 | |
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| 0.0089 | 3.2609 | 675 | 0.0092 | |
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| 0.0087 | 3.3816 | 700 | 0.0088 | |
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| 0.0083 | 3.5024 | 725 | 0.0088 | |
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| 0.0088 | 3.6232 | 750 | 0.0080 | |
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| 0.0058 | 3.7440 | 775 | 0.0069 | |
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| 0.008 | 3.8647 | 800 | 0.0070 | |
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| 0.0099 | 3.9855 | 825 | 0.0073 | |
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| 0.0072 | 4.1063 | 850 | 0.0113 | |
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| 0.0065 | 4.2271 | 875 | 0.0107 | |
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| 0.0079 | 4.3478 | 900 | 0.0097 | |
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| 0.0081 | 4.4686 | 925 | 0.0103 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.46.1 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
