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--- |
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base_model: meta-llama/Llama-2-7b-hf |
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tags: |
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- generated_from_trainer |
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datasets: |
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- glue |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: Llama-2-7b-hf-finetuned-mrpc-v5 |
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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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# Llama-2-7b-hf-finetuned-mrpc-v5 |
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This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6070 |
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- Accuracy: 0.8480 |
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- F1: 0.8916 |
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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: 2e-05 |
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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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- 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: 12 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss | |
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|:-------------:|:-----:|:-----:|:--------:|:------:|:---------------:| |
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| 0.733 | 1.0 | 917 | 0.6912 | 0.7974 | 0.6016 | |
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| 0.6103 | 2.0 | 1834 | 0.7402 | 0.8339 | 0.5650 | |
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| 0.508 | 3.0 | 2751 | 0.7525 | 0.8358 | 0.5246 | |
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| 0.5354 | 4.0 | 3668 | 0.7794 | 0.8529 | 0.5318 | |
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| 0.4246 | 5.0 | 4585 | 0.7843 | 0.8508 | 0.5279 | |
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| 0.4295 | 6.0 | 5502 | 0.7966 | 0.8591 | 0.5248 | |
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| 0.4473 | 7.0 | 6419 | 0.8162 | 0.8696 | 0.5169 | |
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| 0.419 | 8.0 | 7336 | 0.8260 | 0.8778 | 0.5552 | |
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| 0.3876 | 9.0 | 8253 | 0.8284 | 0.8776 | 0.5514 | |
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| 0.42 | 10.0 | 9170 | 0.5576 | 0.8407 | 0.8862 | |
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| 0.3678 | 11.0 | 10087 | 0.6212 | 0.8480 | 0.8927 | |
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| 0.3453 | 12.0 | 11004 | 0.6070 | 0.8480 | 0.8916 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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