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bert-large-cased-finetuned-fce
This model is a fine-tuned version of bert-large-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5307
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: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9048 | 1.0 | 122 | 1.6691 |
| 1.6505 | 2.0 | 244 | 1.5172 |
| 1.5615 | 3.0 | 366 | 1.5019 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
