gpt2-medium-shakes-pear
This model is a fine-tuned version of gpt2-medium on the None dataset. It achieves the following results on the evaluation set:
- Loss: 10.6437
- Rouge1: 0.0723
- Rouge2: 0.0
- Rougel: 0.0723
- Rougelsum: 0.0723
- Bert Precision: 0.7316
- Bert Recall: 0.8011
- Bert F1: 0.7647
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bert Precision | Bert Recall | Bert F1 |
|---|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 1 | 11.4526 | 0.1143 | 0.0 | 0.1143 | 0.1143 | 0.7094 | 0.8058 | 0.7545 |
| No log | 2.0 | 2 | 10.6437 | 0.0723 | 0.0 | 0.0723 | 0.0723 | 0.7316 | 0.8011 | 0.7647 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0