fds
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3905
- Accuracy: 0.56
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.6209 | 1.0 | 38 | 1.4462 | 0.41 |
0.8673 | 2.0 | 76 | 1.1689 | 0.51 |
0.6475 | 3.0 | 114 | 1.3775 | 0.44 |
0.5407 | 4.0 | 152 | 1.3013 | 0.53 |
0.3553 | 5.0 | 190 | 1.7230 | 0.43 |
0.1386 | 6.0 | 228 | 1.8322 | 0.51 |
0.0187 | 7.0 | 266 | 2.2416 | 0.5 |
0.0096 | 8.0 | 304 | 2.3357 | 0.53 |
0.0056 | 9.0 | 342 | 2.3856 | 0.56 |
0.0046 | 10.0 | 380 | 2.3905 | 0.56 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
google-bert/bert-base-cased