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gpt2_left_out_switchboard
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 3.9378
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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.983 | 0.24 | 500 | 5.0786 |
| 4.7603 | 0.48 | 1000 | 4.6865 |
| 4.4521 | 0.73 | 1500 | 4.4635 |
| 4.2512 | 0.97 | 2000 | 4.3124 |
| 4.0458 | 1.21 | 2500 | 4.2272 |
| 3.9687 | 1.45 | 3000 | 4.1443 |
| 3.9024 | 1.69 | 3500 | 4.0705 |
| 3.8439 | 1.93 | 4000 | 4.0057 |
| 3.6791 | 2.18 | 4500 | 3.9845 |
| 3.6259 | 2.42 | 5000 | 3.9471 |
| 3.6137 | 2.66 | 5500 | 3.9057 |
| 3.592 | 2.9 | 6000 | 3.8654 |
| 3.4438 | 3.14 | 6500 | 3.8758 |
| 3.3844 | 3.38 | 7000 | 3.8570 |
| 3.3977 | 3.63 | 7500 | 3.8324 |
| 3.4015 | 3.87 | 8000 | 3.8053 |
| 3.2638 | 4.11 | 8500 | 3.8300 |
| 3.1771 | 4.35 | 9000 | 3.8250 |
| 3.1914 | 4.59 | 9500 | 3.8070 |
| 3.1993 | 4.84 | 10000 | 3.7853 |
| 3.1089 | 5.08 | 10500 | 3.8146 |
| 2.9539 | 5.32 | 11000 | 3.8262 |
| 2.9853 | 5.56 | 11500 | 3.8173 |
| 2.9984 | 5.8 | 12000 | 3.8020 |
| 2.9462 | 6.04 | 12500 | 3.8259 |
| 2.7343 | 6.29 | 13000 | 3.8527 |
| 2.7724 | 6.53 | 13500 | 3.8499 |
| 2.7817 | 6.77 | 14000 | 3.8423 |
| 2.7789 | 7.01 | 14500 | 3.8510 |
| 2.5477 | 7.25 | 15000 | 3.8873 |
| 2.5643 | 7.5 | 15500 | 3.8904 |
| 2.5842 | 7.74 | 16000 | 3.8896 |
| 2.5913 | 7.98 | 16500 | 3.8858 |
| 2.4293 | 8.22 | 17000 | 3.9177 |
| 2.4253 | 8.46 | 17500 | 3.9231 |
| 2.4274 | 8.7 | 18000 | 3.9240 |
| 2.4331 | 8.95 | 18500 | 3.9254 |
| 2.362 | 9.19 | 19000 | 3.9346 |
| 2.3519 | 9.43 | 19500 | 3.9373 |
| 2.3498 | 9.67 | 20000 | 3.9378 |
| 2.3461 | 9.91 | 20500 | 3.9378 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
