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gpt2-gpt2-TF-weight1-epoch15
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 6.0647
- Cls loss: 2.1295
- Lm loss: 3.9339
- Cls Accuracy: 0.8375
- Cls F1: 0.8368
- Cls Precision: 0.8381
- Cls Recall: 0.8375
- Perplexity: 51.11
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: 15
Training results
| Training Loss | Epoch | Step | Cls loss | Cls Accuracy | Cls F1 | Cls Precision | Cls Recall | Lm loss | Perplexity | Validation Loss |
|---|---|---|---|---|---|---|---|---|---|---|
| 4.8702 | 1.0 | 3470 | 0.6951 | 0.7752 | 0.7670 | 0.7978 | 0.7752 | 4.0201 | 55.71 | 4.7157 |
| 4.5856 | 2.0 | 6940 | 0.6797 | 0.8352 | 0.8333 | 0.8406 | 0.8352 | 3.9868 | 53.88 | 4.6669 |
| 4.4147 | 3.0 | 10410 | 0.6899 | 0.8375 | 0.8368 | 0.8384 | 0.8375 | 3.9716 | 53.07 | 4.6619 |
| 4.2479 | 4.0 | 13880 | 0.8678 | 0.8403 | 0.8396 | 0.8413 | 0.8403 | 3.9622 | 52.57 | 4.8305 |
| 4.1281 | 5.0 | 17350 | 0.9747 | 0.8340 | 0.8334 | 0.8346 | 0.8340 | 3.9596 | 52.44 | 4.9349 |
| Training Loss | Epoch | Step | Validation Loss | Cls loss | Lm loss | Cls Accuracy | Cls F1 | Cls Precision | Cls Recall | Perplexity |
|---|---|---|---|---|---|---|---|---|---|---|
| 4.195 | 6.0 | 20820 | 4.9303 | 0.9770 | 3.9528 | 0.8300 | 0.8299 | 0.8299 | 0.8300 | 52.08 |
| 4.0645 | 7.0 | 24290 | 5.0425 | 1.0979 | 3.9440 | 0.8317 | 0.8313 | 0.8317 | 0.8317 | 51.62 |
| 3.9637 | 8.0 | 27760 | 5.3955 | 1.4533 | 3.9414 | 0.8329 | 0.8325 | 0.8328 | 0.8329 | 51.49 |
| 3.9094 | 9.0 | 31230 | 5.6029 | 1.6645 | 3.9375 | 0.8231 | 0.8233 | 0.8277 | 0.8231 | 51.29 |
| 3.8661 | 10.0 | 34700 | 5.8175 | 1.8821 | 3.9344 | 0.8144 | 0.8115 | 0.8222 | 0.8144 | 51.13 |
| 3.8357 | 11.0 | 38170 | 5.6824 | 1.7494 | 3.9319 | 0.8340 | 0.8336 | 0.8342 | 0.8340 | 51.01 |
| 3.8019 | 12.0 | 41640 | 5.8509 | 1.9167 | 3.9332 | 0.8369 | 0.8357 | 0.8396 | 0.8369 | 51.07 |
| 3.7815 | 13.0 | 45110 | 5.9044 | 1.9686 | 3.9346 | 0.8409 | 0.8407 | 0.8408 | 0.8409 | 51.14 |
| 3.7662 | 14.0 | 48580 | 6.0088 | 2.0738 | 3.9337 | 0.8363 | 0.8359 | 0.8364 | 0.8363 | 51.10 |
| 3.7524 | 15.0 | 52050 | 6.0647 | 2.1295 | 3.9339 | 0.8375 | 0.8368 | 0.8381 | 0.8375 | 51.11 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
