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bert-base-uncased-classification-seq2seq
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 14.625
- Accuracy: 0.1667
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0056 | 1.0 | 2500 | 12.4694 | 0.1667 |
| 0.0015 | 2.0 | 5000 | 13.2865 | 0.1667 |
| 0.0006 | 3.0 | 7500 | 13.8803 | 0.1667 |
| 0.0003 | 4.0 | 10000 | 14.3258 | 0.1667 |
| 0.0002 | 5.0 | 12500 | 14.625 | 0.1667 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
