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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 |
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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 |
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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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- Accuracy: 0.7941 |
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- F1: 0.8571 |
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- Loss: 0.4479 |
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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: 5e-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: 10 |
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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 | 0.7206 | 0.8155 | 0.6045 | |
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| No log | 2.0 | 460 | 0.6912 | 0.8158 | 0.6488 | |
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| 0.6326 | 3.0 | 690 | 0.7279 | 0.8235 | 0.5236 | |
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| 0.6326 | 4.0 | 920 | 0.7255 | 0.8282 | 0.5273 | |
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| 0.5602 | 5.0 | 1150 | 0.7402 | 0.8044 | 0.5246 | |
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| 0.5602 | 6.0 | 1380 | 0.75 | 0.8311 | 0.4893 | |
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| 0.5139 | 7.0 | 1610 | 0.7623 | 0.8289 | 0.4884 | |
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| 0.5139 | 8.0 | 1840 | 0.7402 | 0.8307 | 0.4989 | |
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| 0.4754 | 9.0 | 2070 | 0.7745 | 0.8435 | 0.4732 | |
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| 0.4754 | 10.0 | 2300 | 0.7672 | 0.8403 | 0.4716 | |
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| 0.5407 | 11.0 | 2530 | 0.7598 | 0.8393 | 0.4823 | |
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| 0.5407 | 12.0 | 2760 | 0.7451 | 0.8333 | 0.4782 | |
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| 0.5407 | 13.0 | 2990 | 0.7451 | 0.8333 | 0.4713 | |
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| 0.4951 | 14.0 | 3220 | 0.7819 | 0.8489 | 0.4553 | |
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| 0.4951 | 15.0 | 3450 | 0.7745 | 0.8506 | 0.4591 | |
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| 0.4724 | 16.0 | 3680 | 0.7770 | 0.8423 | 0.4631 | |
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| 0.4724 | 17.0 | 3910 | 0.8015 | 0.8576 | 0.4581 | |
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| 0.4455 | 18.0 | 4140 | 0.7819 | 0.8468 | 0.4548 | |
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| 0.4455 | 19.0 | 4370 | 0.7819 | 0.8484 | 0.4511 | |
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| 0.4354 | 20.0 | 4600 | 0.7941 | 0.8571 | 0.4479 | |
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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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