legalclassBERTlarge
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2222
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.8889 | 0.8 | 500 | 1.7423 |
1.6561 | 1.6 | 1000 | 1.5896 |
1.5418 | 2.4 | 1500 | 1.4876 |
1.4735 | 3.2 | 2000 | 1.4236 |
1.4205 | 4.0 | 2500 | 1.3509 |
1.3694 | 4.8 | 3000 | 1.3100 |
1.3201 | 5.6 | 3500 | 1.2715 |
1.2571 | 6.4 | 4000 | 1.2630 |
1.276 | 7.2 | 4500 | 1.2449 |
1.2483 | 8.0 | 5000 | 1.2222 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
google-bert/bert-base-uncased