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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-v0.4 |
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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-v0.4 |
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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: 0.6354 |
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- Accuracy: 0.8701 |
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- F1: 0.9062 |
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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: 1.2800000000000003e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 40 |
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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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| No log | 1.0 | 230 | 0.6446 | 0.7695 | 0.6542 | |
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| No log | 2.0 | 460 | 0.6912 | 0.7968 | 0.5938 | |
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| 0.6489 | 3.0 | 690 | 0.7230 | 0.8151 | 0.5694 | |
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| 0.6489 | 4.0 | 920 | 0.7230 | 0.8138 | 0.5503 | |
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| 0.5299 | 5.0 | 1150 | 0.7402 | 0.8251 | 0.5492 | |
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| 0.5299 | 6.0 | 1380 | 0.7794 | 0.8432 | 0.4880 | |
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| 0.4687 | 7.0 | 1610 | 0.8064 | 0.8663 | 0.4559 | |
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| 0.4687 | 8.0 | 1840 | 0.8186 | 0.875 | 0.4298 | |
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| 0.374 | 9.0 | 2070 | 0.8284 | 0.8818 | 0.4210 | |
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| 0.374 | 10.0 | 2300 | 0.8456 | 0.8916 | 0.3953 | |
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| 0.3096 | 11.0 | 2530 | 0.8431 | 0.8897 | 0.4074 | |
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| 0.3096 | 12.0 | 2760 | 0.8407 | 0.8862 | 0.4030 | |
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| 0.3096 | 13.0 | 2990 | 0.8456 | 0.8904 | 0.3982 | |
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| 0.2799 | 14.0 | 3220 | 0.8456 | 0.8881 | 0.3873 | |
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| 0.2799 | 15.0 | 3450 | 0.8529 | 0.8940 | 0.3939 | |
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| 0.2511 | 16.0 | 3680 | 0.8431 | 0.8877 | 0.4018 | |
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| 0.2511 | 17.0 | 3910 | 0.8529 | 0.8947 | 0.3969 | |
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| 0.2371 | 18.0 | 4140 | 0.8456 | 0.8912 | 0.3963 | |
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| 0.2371 | 19.0 | 4370 | 0.8578 | 0.8964 | 0.3865 | |
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| 0.2211 | 20.0 | 4600 | 0.8505 | 0.8928 | 0.4165 | |
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| 0.2211 | 21.0 | 4830 | 0.8456 | 0.8901 | 0.4070 | |
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| 0.2136 | 22.0 | 5060 | 0.8578 | 0.8972 | 0.4090 | |
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| 0.2136 | 23.0 | 5290 | 0.8578 | 0.8961 | 0.4328 | |
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| 0.1774 | 24.0 | 5520 | 0.8382 | 0.8791 | 0.4602 | |
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| 0.1774 | 25.0 | 5750 | 0.8627 | 0.9018 | 0.4551 | |
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| 0.1774 | 26.0 | 5980 | 0.8505 | 0.8920 | 0.4677 | |
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| 0.1521 | 27.0 | 6210 | 0.8578 | 0.8953 | 0.4854 | |
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| 0.1521 | 28.0 | 6440 | 0.8505 | 0.8932 | 0.5064 | |
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| 0.134 | 29.0 | 6670 | 0.8603 | 0.8988 | 0.4971 | |
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| 0.134 | 30.0 | 6900 | 0.8676 | 0.9046 | 0.4717 | |
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| 0.1298 | 31.0 | 7130 | 0.5216 | 0.8652 | 0.8998 | |
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| 0.1298 | 32.0 | 7360 | 0.5339 | 0.8578 | 0.8979 | |
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| 0.1233 | 33.0 | 7590 | 0.5533 | 0.8627 | 0.8993 | |
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| 0.1233 | 34.0 | 7820 | 0.5526 | 0.875 | 0.9084 | |
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| 0.1094 | 35.0 | 8050 | 0.6027 | 0.8725 | 0.9068 | |
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| 0.1094 | 36.0 | 8280 | 0.6441 | 0.8652 | 0.9037 | |
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| 0.0906 | 37.0 | 8510 | 0.6289 | 0.8554 | 0.8929 | |
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| 0.0906 | 38.0 | 8740 | 0.6213 | 0.8676 | 0.9039 | |
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| 0.0906 | 39.0 | 8970 | 0.6585 | 0.8603 | 0.8977 | |
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| 0.0842 | 40.0 | 9200 | 0.6354 | 0.8701 | 0.9062 | |
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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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