| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: Romance-cleaned-3 |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # Romance-cleaned-3 |
| |
|
| | This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 4.9593 |
| |
|
| | ## 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: 5e-05 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 32 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 8 |
| | - total_train_batch_size: 256 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_steps: 1000 |
| | - num_epochs: 50 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | No log | 1.0 | 16 | 10.0173 | |
| | | No log | 2.0 | 32 | 9.1598 | |
| | | No log | 3.0 | 48 | 8.6820 | |
| | | No log | 4.0 | 64 | 8.3963 | |
| | | No log | 5.0 | 80 | 8.1259 | |
| | | No log | 6.0 | 96 | 7.9259 | |
| | | No log | 7.0 | 112 | 7.6943 | |
| | | No log | 8.0 | 128 | 7.4803 | |
| | | No log | 9.0 | 144 | 7.2883 | |
| | | No log | 10.0 | 160 | 7.1145 | |
| | | No log | 11.0 | 176 | 6.9568 | |
| | | No log | 12.0 | 192 | 6.8000 | |
| | | No log | 13.0 | 208 | 6.6515 | |
| | | No log | 14.0 | 224 | 6.5033 | |
| | | No log | 15.0 | 240 | 6.3471 | |
| | | No log | 16.0 | 256 | 6.2029 | |
| | | No log | 17.0 | 272 | 6.0583 | |
| | | No log | 18.0 | 288 | 5.9173 | |
| | | No log | 19.0 | 304 | 5.7819 | |
| | | No log | 20.0 | 320 | 5.6710 | |
| | | No log | 21.0 | 336 | 5.5588 | |
| | | No log | 22.0 | 352 | 5.4729 | |
| | | No log | 23.0 | 368 | 5.3980 | |
| | | No log | 24.0 | 384 | 5.3261 | |
| | | No log | 25.0 | 400 | 5.2801 | |
| | | No log | 26.0 | 416 | 5.2317 | |
| | | No log | 27.0 | 432 | 5.1942 | |
| | | No log | 28.0 | 448 | 5.1523 | |
| | | No log | 29.0 | 464 | 5.1235 | |
| | | No log | 30.0 | 480 | 5.1008 | |
| | | No log | 31.0 | 496 | 5.0667 | |
| | | No log | 32.0 | 512 | 5.0472 | |
| | | No log | 33.0 | 528 | 5.0252 | |
| | | No log | 34.0 | 544 | 5.0143 | |
| | | No log | 35.0 | 560 | 5.0049 | |
| | | No log | 36.0 | 576 | 4.9938 | |
| | | No log | 37.0 | 592 | 4.9827 | |
| | | No log | 38.0 | 608 | 4.9719 | |
| | | No log | 39.0 | 624 | 4.9666 | |
| | | No log | 40.0 | 640 | 4.9540 | |
| | | No log | 41.0 | 656 | 4.9549 | |
| | | No log | 42.0 | 672 | 4.9485 | |
| | | No log | 43.0 | 688 | 4.9602 | |
| | | No log | 44.0 | 704 | 4.9464 | |
| | | No log | 45.0 | 720 | 4.9592 | |
| | | No log | 46.0 | 736 | 4.9611 | |
| | | No log | 47.0 | 752 | 4.9558 | |
| | | No log | 48.0 | 768 | 4.9659 | |
| | | No log | 49.0 | 784 | 4.9739 | |
| | | No log | 50.0 | 800 | 4.9593 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.23.1 |
| | - Pytorch 1.12.1+cu113 |
| | - Datasets 2.6.1 |
| | - Tokenizers 0.13.1 |
| |
|
