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_nov14
results: []
clause_model_nov14
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: 0.0520
- Accuracy: 0.9917
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 |
|---|---|---|---|---|
| 1.5312 | 1.0 | 1179 | 0.8775 | 0.795 |
| 0.6044 | 2.0 | 2358 | 0.3375 | 0.9192 |
| 0.2778 | 3.0 | 3537 | 0.1704 | 0.9625 |
| 0.162 | 4.0 | 4716 | 0.1016 | 0.9792 |
| 0.121 | 5.0 | 5895 | 0.0791 | 0.9842 |
| 0.0748 | 6.0 | 7074 | 0.0596 | 0.9875 |
| 0.0705 | 7.0 | 8253 | 0.0618 | 0.9917 |
| 0.052 | 8.0 | 9432 | 0.0622 | 0.9908 |
| 0.0299 | 9.0 | 10611 | 0.0505 | 0.9917 |
| 0.031 | 10.0 | 11790 | 0.0520 | 0.9917 |
Framework versions
- Transformers 4.42.0
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1