--- library_name: transformers license: mit base_model: gpt2 tags: - generated_from_trainer model-index: - name: tfa_output_2025_m02_d02_t23h_28m_54s results: [] --- # tfa_output_2025_m02_d02_t23h_28m_54s This model is a fine-tuned version of [gpt2](https://huggingface.co./gpt2) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.4602 ## 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: 1e-06 - train_batch_size: 2 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.PAGED_ADAMW with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: constant_with_warmup - lr_scheduler_warmup_ratio: 0.05 - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-------:|:----:|:---------------:| | No log | 0 | 0 | 3.1242 | | 3.7239 | 0.5714 | 1 | 3.1242 | | 4.5819 | 1.5714 | 2 | 3.1012 | | 4.5655 | 2.5714 | 3 | 3.0775 | | 4.5318 | 3.5714 | 4 | 3.0655 | | 4.5864 | 4.5714 | 5 | 3.0469 | | 4.4551 | 5.5714 | 6 | 3.0325 | | 4.4845 | 6.5714 | 7 | 3.0158 | | 4.5483 | 7.5714 | 8 | 3.0042 | | 4.4145 | 8.5714 | 9 | 2.9926 | | 4.4484 | 9.5714 | 10 | 2.9827 | | 4.3074 | 10.5714 | 11 | 2.9709 | | 4.3609 | 11.5714 | 12 | 2.9587 | | 4.3821 | 12.5714 | 13 | 2.9485 | | 4.386 | 13.5714 | 14 | 2.9399 | | 4.3846 | 14.5714 | 15 | 2.9299 | | 4.3531 | 15.5714 | 16 | 2.9202 | | 4.3193 | 16.5714 | 17 | 2.9091 | | 4.2898 | 17.5714 | 18 | 2.9001 | | 4.3685 | 18.5714 | 19 | 2.8888 | | 4.232 | 19.5714 | 20 | 2.8802 | | 4.2805 | 20.5714 | 21 | 2.8718 | | 4.275 | 21.5714 | 22 | 2.8589 | | 4.2062 | 22.5714 | 23 | 2.8513 | | 4.1492 | 23.5714 | 24 | 2.8427 | | 4.1998 | 24.5714 | 25 | 2.8323 | | 4.1638 | 25.5714 | 26 | 2.8219 | | 4.1229 | 26.5714 | 27 | 2.8149 | | 4.2027 | 27.5714 | 28 | 2.8057 | | 4.1399 | 28.5714 | 29 | 2.7971 | | 4.1457 | 29.5714 | 30 | 2.7907 | | 4.1507 | 30.5714 | 31 | 2.7815 | | 4.0924 | 31.5714 | 32 | 2.7740 | | 4.1176 | 32.5714 | 33 | 2.7660 | | 4.1109 | 33.5714 | 34 | 2.7583 | | 3.9774 | 34.5714 | 35 | 2.7497 | | 4.0628 | 35.5714 | 36 | 2.7429 | | 4.0824 | 36.5714 | 37 | 2.7344 | | 4.0686 | 37.5714 | 38 | 2.7263 | | 4.0403 | 38.5714 | 39 | 2.7191 | | 4.0444 | 39.5714 | 40 | 2.7140 | | 3.9816 | 40.5714 | 41 | 2.7064 | | 3.9371 | 41.5714 | 42 | 2.6999 | | 3.9101 | 42.5714 | 43 | 2.6939 | | 3.9853 | 43.5714 | 44 | 2.6860 | | 3.9293 | 44.5714 | 45 | 2.6800 | | 3.8705 | 45.5714 | 46 | 2.6748 | | 3.9374 | 46.5714 | 47 | 2.6683 | | 3.8989 | 47.5714 | 48 | 2.6611 | | 3.9209 | 48.5714 | 49 | 2.6557 | | 3.8378 | 49.5714 | 50 | 2.6503 | | 3.9311 | 50.5714 | 51 | 2.6434 | | 3.8503 | 51.5714 | 52 | 2.6379 | | 3.7551 | 52.5714 | 53 | 2.6334 | | 3.757 | 53.5714 | 54 | 2.6291 | | 3.8337 | 54.5714 | 55 | 2.6228 | | 3.8533 | 55.5714 | 56 | 2.6176 | | 3.7737 | 56.5714 | 57 | 2.6125 | | 3.7589 | 57.5714 | 58 | 2.6064 | | 3.7929 | 58.5714 | 59 | 2.6018 | | 3.7802 | 59.5714 | 60 | 2.5972 | | 3.824 | 60.5714 | 61 | 2.5932 | | 3.7761 | 61.5714 | 62 | 2.5883 | | 3.7067 | 62.5714 | 63 | 2.5848 | | 3.7647 | 63.5714 | 64 | 2.5791 | | 3.6702 | 64.5714 | 65 | 2.5760 | | 3.7744 | 65.5714 | 66 | 2.5721 | | 3.7251 | 66.5714 | 67 | 2.5674 | | 3.6592 | 67.5714 | 68 | 2.5618 | | 3.8159 | 68.5714 | 69 | 2.5583 | | 3.6529 | 69.5714 | 70 | 2.5554 | | 3.6874 | 70.5714 | 71 | 2.5510 | | 3.6516 | 71.5714 | 72 | 2.5466 | | 3.5826 | 72.5714 | 73 | 2.5438 | | 3.6663 | 73.5714 | 74 | 2.5397 | | 3.6507 | 74.5714 | 75 | 2.5351 | | 3.591 | 75.5714 | 76 | 2.5343 | | 3.6226 | 76.5714 | 77 | 2.5294 | | 3.5843 | 77.5714 | 78 | 2.5260 | | 3.6361 | 78.5714 | 79 | 2.5216 | | 3.5118 | 79.5714 | 80 | 2.5197 | | 3.6315 | 80.5714 | 81 | 2.5154 | | 3.5687 | 81.5714 | 82 | 2.5112 | | 3.5679 | 82.5714 | 83 | 2.5103 | | 3.4985 | 83.5714 | 84 | 2.5059 | | 3.5778 | 84.5714 | 85 | 2.5034 | | 3.5422 | 85.5714 | 86 | 2.5003 | | 3.6483 | 86.5714 | 87 | 2.4969 | | 3.5949 | 87.5714 | 88 | 2.4933 | | 3.5475 | 88.5714 | 89 | 2.4904 | | 3.5944 | 89.5714 | 90 | 2.4861 | | 3.5698 | 90.5714 | 91 | 2.4841 | | 3.5287 | 91.5714 | 92 | 2.4832 | | 3.5029 | 92.5714 | 93 | 2.4792 | | 3.4956 | 93.5714 | 94 | 2.4758 | | 3.5941 | 94.5714 | 95 | 2.4739 | | 3.4637 | 95.5714 | 96 | 2.4710 | | 3.5336 | 96.5714 | 97 | 2.4683 | | 3.4492 | 97.5714 | 98 | 2.4661 | | 3.4548 | 98.5714 | 99 | 2.4624 | | 3.5259 | 99.5714 | 100 | 2.4602 | ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0