| | --- |
| | library_name: transformers |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - bleu |
| | model-index: |
| | - name: rotating-head-lr-norm-gpt2-medium-wikitext |
| | 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. --> |
| |
|
| | # rotating-head-lr-norm-gpt2-medium-wikitext |
| |
|
| | This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 3.2154 |
| | - Accuracy: 0.4186 |
| | - Perplexity: 24.9126 |
| | - Bleu: 0.1314 |
| |
|
| | ## 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: 0.0001 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 5 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Perplexity | Bleu | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:|:----------:|:------:| |
| | | 5.9061 | 0.2806 | 500 | 5.7498 | 0.2230 | 314.1125 | 0.0496 | |
| | | 4.8622 | 0.5612 | 1000 | 4.7414 | 0.2810 | 114.5910 | 0.0705 | |
| | | 4.3006 | 0.8418 | 1500 | 4.2267 | 0.3182 | 68.4878 | 0.0834 | |
| | | 3.9714 | 1.1223 | 2000 | 3.9429 | 0.3439 | 51.5654 | 0.0924 | |
| | | 3.7835 | 1.4029 | 2500 | 3.7523 | 0.3629 | 42.6192 | 0.0969 | |
| | | 3.6732 | 1.6835 | 3000 | 3.6293 | 0.3750 | 37.6861 | 0.1067 | |
| | | 3.5764 | 1.9641 | 3500 | 3.5353 | 0.3848 | 34.3055 | 0.1124 | |
| | | 3.4733 | 2.2447 | 4000 | 3.4822 | 0.3899 | 32.5321 | 0.1183 | |
| | | 3.4163 | 2.5253 | 4500 | 3.4356 | 0.3946 | 31.0488 | 0.1253 | |
| | | 3.3818 | 2.8058 | 5000 | 3.3806 | 0.4006 | 29.3886 | 0.1215 | |
| | | 3.2827 | 3.0864 | 5500 | 3.3539 | 0.4028 | 28.6152 | 0.1308 | |
| | | 3.2712 | 3.3670 | 6000 | 3.3233 | 0.4067 | 27.7517 | 0.1289 | |
| | | 3.247 | 3.6476 | 6500 | 3.2908 | 0.4098 | 26.8652 | 0.1304 | |
| | | 3.2203 | 3.9282 | 7000 | 3.2657 | 0.4126 | 26.1980 | 0.1278 | |
| | | 3.1558 | 4.2088 | 7500 | 3.2440 | 0.4152 | 25.6357 | 0.1319 | |
| | | 3.1152 | 4.4893 | 8000 | 3.2283 | 0.4169 | 25.2358 | 0.1301 | |
| | | 3.1228 | 4.7699 | 8500 | 3.2154 | 0.4186 | 24.9126 | 0.1314 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.49.0 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.3.2 |
| | - Tokenizers 0.21.0 |
| | |
