metadata
license: cc-by-sa-4.0
base_model: nlpaueb/bert-base-uncased-contracts
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: clause_model
results: []
clause_model
This model is a fine-tuned version of nlpaueb/bert-base-uncased-contracts on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5961
- Accuracy: 0.8955
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.0237 | 1.0 | 883 | 0.9479 | 0.7783 |
| 0.6024 | 2.0 | 1766 | 0.5360 | 0.8713 |
| 0.2674 | 3.0 | 2649 | 0.5095 | 0.8866 |
| 0.1629 | 4.0 | 3532 | 0.5706 | 0.8904 |
| 0.1027 | 5.0 | 4415 | 0.5767 | 0.8866 |
| 0.0724 | 6.0 | 5298 | 0.5502 | 0.8955 |
| 0.0646 | 7.0 | 6181 | 0.5825 | 0.8917 |
| 0.0458 | 8.0 | 7064 | 0.6150 | 0.8981 |
| 0.0359 | 9.0 | 7947 | 0.5936 | 0.8955 |
| 0.0268 | 10.0 | 8830 | 0.5961 | 0.8955 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1