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bert-concat-3
This model is a fine-tuned version of on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 5.8028
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: 35
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.5215 | 2.11 | 1000 | 6.1057 |
| 5.9958 | 4.22 | 2000 | 6.0199 |
| 5.9066 | 6.33 | 3000 | 5.9833 |
| 5.8449 | 8.44 | 4000 | 5.9594 |
| 5.7913 | 10.55 | 5000 | 5.9176 |
| 5.7418 | 12.66 | 6000 | 5.8949 |
| 5.6901 | 14.77 | 7000 | 5.8753 |
| 5.6485 | 16.88 | 8000 | 5.8592 |
| 5.6238 | 18.99 | 9000 | 5.8509 |
| 5.6704 | 21.1 | 10000 | 5.8856 |
| 5.6375 | 23.21 | 11000 | 5.8703 |
| 5.6039 | 25.32 | 12000 | 5.8635 |
| 5.5756 | 27.43 | 13000 | 5.8533 |
| 5.5437 | 29.54 | 14000 | 5.8408 |
| 5.5189 | 31.65 | 15000 | 5.8154 |
| 5.4982 | 33.76 | 16000 | 5.8028 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
