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bert-large-cased-finetuned-prompt-20
This model is a fine-tuned version of bert-large-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7142
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.3173 | 1.0 | 280 | 1.1293 |
1.087 | 2.0 | 560 | 0.9716 |
1.0064 | 3.0 | 840 | 0.9606 |
0.9341 | 4.0 | 1120 | 0.8887 |
0.8881 | 5.0 | 1400 | 0.8654 |
0.8662 | 6.0 | 1680 | 0.8181 |
0.8331 | 7.0 | 1960 | 0.8286 |
0.8206 | 8.0 | 2240 | 0.7941 |
0.8017 | 9.0 | 2520 | 0.7677 |
0.772 | 10.0 | 2800 | 0.7711 |
0.76 | 11.0 | 3080 | 0.7314 |
0.7436 | 12.0 | 3360 | 0.7479 |
0.7305 | 13.0 | 3640 | 0.7354 |
0.7204 | 14.0 | 3920 | 0.7143 |
0.7102 | 15.0 | 4200 | 0.7366 |
0.7034 | 16.0 | 4480 | 0.7036 |
0.6937 | 17.0 | 4760 | 0.7049 |
0.695 | 18.0 | 5040 | 0.7080 |
0.6923 | 19.0 | 5320 | 0.7110 |
0.6886 | 20.0 | 5600 | 0.6969 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2