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--- |
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license: llama3 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: meta-llama/Meta-Llama-3-8B |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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model-index: |
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- name: Llama3_8B_Task2_semantic_pred |
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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_8B_Task2_semantic_pred |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2767 |
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- Accuracy: 0.6493 |
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- Precision: 0.6493 |
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- Recall: 0.6493 |
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- F1 score: 0.6493 |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | F1 score | Precision | Recall | Validation Loss | |
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|:-------------:|:------:|:----:|:--------:|:--------:|:---------:|:------:|:---------------:| |
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| 0.49 | 0.5208 | 200 | 0.5750 | 0.5750 | 0.5750 | 0.5750 | 0.9015 | |
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| 0.439 | 1.0417 | 400 | 0.5541 | 0.5541 | 0.5541 | 0.5541 | 1.2361 | |
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| 0.2744 | 1.5625 | 600 | 0.7744 | 0.7744 | 0.7744 | 0.7744 | 0.4804 | |
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| 0.2621 | 2.0833 | 800 | 0.5658 | 0.5658 | 0.5658 | 0.5658 | 1.2460 | |
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| 0.1921 | 2.6042 | 1000 | 0.6102 | 0.6102 | 0.6102 | 0.6102 | 1.0217 | |
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| 0.1602 | 3.125 | 1200 | 0.5880 | 0.5880 | 0.5880 | 0.5880 | 1.3196 | |
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| 0.1736 | 3.6458 | 1400 | 0.5684 | 0.5684 | 0.5684 | 0.5684 | 1.7235 | |
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| 0.1628 | 4.1667 | 1600 | 0.6780 | 0.6780 | 0.6780 | 0.6780 | 1.0542 | |
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| 0.1204 | 4.6875 | 1800 | 1.2767 | 0.6493 | 0.6493 | 0.6493 | 0.6493 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.44.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
