gpt2-gpt2-TF-weight1-epoch5-with-eval
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.9349
- Cls loss: 0.9747
- Lm loss: 3.9596
- Cls Accuracy: 0.8340
- Cls F1: 0.8334
- Cls Precision: 0.8346
- Cls Recall: 0.8340
- Perplexity: 52.44
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Cls loss | Lm loss | Cls Accuracy | Cls F1 | Cls Precision | Cls Recall | Perplexity |
---|---|---|---|---|---|---|---|---|---|---|
4.8702 | 1.0 | 3470 | 4.7157 | 0.6951 | 4.0201 | 0.7752 | 0.7670 | 0.7978 | 0.7752 | 55.71 |
4.5856 | 2.0 | 6940 | 4.6669 | 0.6797 | 3.9868 | 0.8352 | 0.8333 | 0.8406 | 0.8352 | 53.88 |
4.4147 | 3.0 | 10410 | 4.6619 | 0.6899 | 3.9716 | 0.8375 | 0.8368 | 0.8384 | 0.8375 | 53.07 |
4.2479 | 4.0 | 13880 | 4.8305 | 0.8678 | 3.9622 | 0.8403 | 0.8396 | 0.8413 | 0.8403 | 52.57 |
4.1281 | 5.0 | 17350 | 4.9349 | 0.9747 | 3.9596 | 0.8340 | 0.8334 | 0.8346 | 0.8340 | 52.44 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
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