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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 relianceV2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0118 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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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: 5.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.0395 | 0.2424 | 5 | 0.0433 | |
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| 0.0324 | 0.4848 | 10 | 0.0300 | |
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| 0.024 | 0.7273 | 15 | 0.0244 | |
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| 0.0189 | 0.9697 | 20 | 0.0212 | |
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| 0.0171 | 1.2303 | 25 | 0.0190 | |
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| 0.0146 | 1.4727 | 30 | 0.0173 | |
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| 0.0144 | 1.7152 | 35 | 0.0161 | |
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| 0.0104 | 1.9576 | 40 | 0.0155 | |
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| 0.0143 | 2.2182 | 45 | 0.0152 | |
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| 0.0117 | 2.4606 | 50 | 0.0141 | |
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| 0.015 | 2.7030 | 55 | 0.0136 | |
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| 0.0092 | 2.9455 | 60 | 0.0131 | |
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| 0.008 | 3.2061 | 65 | 0.0127 | |
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| 0.0109 | 3.4485 | 70 | 0.0125 | |
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| 0.0085 | 3.6909 | 75 | 0.0122 | |
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| 0.0089 | 3.9333 | 80 | 0.0120 | |
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| 0.0074 | 4.1939 | 85 | 0.0118 | |
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| 0.0074 | 4.4364 | 90 | 0.0118 | |
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| 0.0066 | 4.6788 | 95 | 0.0118 | |
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| 0.0065 | 4.9212 | 100 | 0.0118 | |
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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 |
