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--- |
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library_name: peft |
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license: llama3.1 |
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base_model: meta-llama/Llama-3.1-8B-Instruct |
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tags: |
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- base_model:adapter:meta-llama/Llama-3.1-8B-Instruct |
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- lora |
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- transformers |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: llama3_ft_section_classifier |
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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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# llama3_ft_section_classifier |
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This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.3342 |
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- Accuracy: 0.6232 |
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- Precision: 0.6126 |
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- Recall: 0.6232 |
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- F1: 0.6164 |
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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: 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_FUSED 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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 16.483 | 1.0 | 275 | 1.3758 | 0.5423 | 0.5769 | 0.5423 | 0.5311 | |
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| 9.7264 | 2.0 | 550 | 1.1577 | 0.6095 | 0.6215 | 0.6095 | 0.6065 | |
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| 8.2372 | 3.0 | 825 | 1.1713 | 0.6041 | 0.6264 | 0.6041 | 0.6061 | |
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| 6.1069 | 4.0 | 1100 | 1.2993 | 0.6123 | 0.6090 | 0.6123 | 0.6025 | |
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| 3.1467 | 5.0 | 1375 | 1.5804 | 0.6027 | 0.6255 | 0.6027 | 0.6085 | |
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| 1.3995 | 6.0 | 1650 | 1.9973 | 0.6077 | 0.6005 | 0.6077 | 0.5994 | |
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| 0.8489 | 7.0 | 1925 | 2.3380 | 0.6082 | 0.6070 | 0.6082 | 0.5990 | |
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| 0.4705 | 8.0 | 2200 | 2.5919 | 0.6245 | 0.6223 | 0.6245 | 0.6172 | |
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| 0.186 | 9.0 | 2475 | 2.8240 | 0.6223 | 0.6275 | 0.6223 | 0.6238 | |
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| 0.0636 | 10.0 | 2750 | 3.0796 | 0.6209 | 0.6273 | 0.6209 | 0.6190 | |
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| 0.0248 | 11.0 | 3025 | 3.2076 | 0.6259 | 0.6269 | 0.6259 | 0.6231 | |
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| 0.0009 | 12.0 | 3300 | 3.2148 | 0.6214 | 0.6133 | 0.6214 | 0.6158 | |
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| 0.0001 | 13.0 | 3575 | 3.2700 | 0.6209 | 0.6132 | 0.6209 | 0.6158 | |
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| 0.0 | 14.0 | 3850 | 3.2962 | 0.6223 | 0.6124 | 0.6223 | 0.6158 | |
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| 0.0 | 15.0 | 4125 | 3.3102 | 0.6223 | 0.6118 | 0.6223 | 0.6156 | |
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| 0.0 | 16.0 | 4400 | 3.3219 | 0.6236 | 0.6138 | 0.6236 | 0.6173 | |
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| 0.0 | 17.0 | 4675 | 3.3271 | 0.6232 | 0.6125 | 0.6232 | 0.6162 | |
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| 0.0 | 18.0 | 4950 | 3.3285 | 0.6218 | 0.6108 | 0.6218 | 0.6148 | |
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| 0.0 | 19.0 | 5225 | 3.3359 | 0.6232 | 0.6126 | 0.6232 | 0.6163 | |
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| 0.0 | 20.0 | 5500 | 3.3342 | 0.6232 | 0.6126 | 0.6232 | 0.6164 | |
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### Framework versions |
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- PEFT 0.17.1 |
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- Transformers 4.57.1 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.1 |
