--- base_model: meta-llama/Llama-2-7b-hf tags: - generated_from_trainer datasets: - glue metrics: - accuracy - f1 model-index: - name: Llama-2-7b-hf-finetuned-mrpc-v0.4 results: [] --- # Llama-2-7b-hf-finetuned-mrpc-v0.4 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. It achieves the following results on the evaluation set: - Loss: 0.6354 - Accuracy: 0.8701 - F1: 0.9062 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1.2800000000000003e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 40 ### Training results | Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss | |:-------------:|:-----:|:----:|:--------:|:------:|:---------------:| | No log | 1.0 | 230 | 0.6446 | 0.7695 | 0.6542 | | No log | 2.0 | 460 | 0.6912 | 0.7968 | 0.5938 | | 0.6489 | 3.0 | 690 | 0.7230 | 0.8151 | 0.5694 | | 0.6489 | 4.0 | 920 | 0.7230 | 0.8138 | 0.5503 | | 0.5299 | 5.0 | 1150 | 0.7402 | 0.8251 | 0.5492 | | 0.5299 | 6.0 | 1380 | 0.7794 | 0.8432 | 0.4880 | | 0.4687 | 7.0 | 1610 | 0.8064 | 0.8663 | 0.4559 | | 0.4687 | 8.0 | 1840 | 0.8186 | 0.875 | 0.4298 | | 0.374 | 9.0 | 2070 | 0.8284 | 0.8818 | 0.4210 | | 0.374 | 10.0 | 2300 | 0.8456 | 0.8916 | 0.3953 | | 0.3096 | 11.0 | 2530 | 0.8431 | 0.8897 | 0.4074 | | 0.3096 | 12.0 | 2760 | 0.8407 | 0.8862 | 0.4030 | | 0.3096 | 13.0 | 2990 | 0.8456 | 0.8904 | 0.3982 | | 0.2799 | 14.0 | 3220 | 0.8456 | 0.8881 | 0.3873 | | 0.2799 | 15.0 | 3450 | 0.8529 | 0.8940 | 0.3939 | | 0.2511 | 16.0 | 3680 | 0.8431 | 0.8877 | 0.4018 | | 0.2511 | 17.0 | 3910 | 0.8529 | 0.8947 | 0.3969 | | 0.2371 | 18.0 | 4140 | 0.8456 | 0.8912 | 0.3963 | | 0.2371 | 19.0 | 4370 | 0.8578 | 0.8964 | 0.3865 | | 0.2211 | 20.0 | 4600 | 0.8505 | 0.8928 | 0.4165 | | 0.2211 | 21.0 | 4830 | 0.8456 | 0.8901 | 0.4070 | | 0.2136 | 22.0 | 5060 | 0.8578 | 0.8972 | 0.4090 | | 0.2136 | 23.0 | 5290 | 0.8578 | 0.8961 | 0.4328 | | 0.1774 | 24.0 | 5520 | 0.8382 | 0.8791 | 0.4602 | | 0.1774 | 25.0 | 5750 | 0.8627 | 0.9018 | 0.4551 | | 0.1774 | 26.0 | 5980 | 0.8505 | 0.8920 | 0.4677 | | 0.1521 | 27.0 | 6210 | 0.8578 | 0.8953 | 0.4854 | | 0.1521 | 28.0 | 6440 | 0.8505 | 0.8932 | 0.5064 | | 0.134 | 29.0 | 6670 | 0.8603 | 0.8988 | 0.4971 | | 0.134 | 30.0 | 6900 | 0.8676 | 0.9046 | 0.4717 | | 0.1298 | 31.0 | 7130 | 0.5216 | 0.8652 | 0.8998 | | 0.1298 | 32.0 | 7360 | 0.5339 | 0.8578 | 0.8979 | | 0.1233 | 33.0 | 7590 | 0.5533 | 0.8627 | 0.8993 | | 0.1233 | 34.0 | 7820 | 0.5526 | 0.875 | 0.9084 | | 0.1094 | 35.0 | 8050 | 0.6027 | 0.8725 | 0.9068 | | 0.1094 | 36.0 | 8280 | 0.6441 | 0.8652 | 0.9037 | | 0.0906 | 37.0 | 8510 | 0.6289 | 0.8554 | 0.8929 | | 0.0906 | 38.0 | 8740 | 0.6213 | 0.8676 | 0.9039 | | 0.0906 | 39.0 | 8970 | 0.6585 | 0.8603 | 0.8977 | | 0.0842 | 40.0 | 9200 | 0.6354 | 0.8701 | 0.9062 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.13.3