clause_model2
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: 0.9374
- Accuracy: 0.8600
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 |
---|---|---|---|---|
1.504 | 1.0 | 1197 | 0.9127 | 0.7885 |
0.6679 | 2.0 | 2394 | 0.6784 | 0.8421 |
0.352 | 3.0 | 3591 | 0.7073 | 0.8402 |
0.2604 | 4.0 | 4788 | 0.7450 | 0.8581 |
0.1907 | 5.0 | 5985 | 0.7920 | 0.8553 |
0.1477 | 6.0 | 7182 | 0.8424 | 0.8609 |
0.1081 | 7.0 | 8379 | 0.9059 | 0.8553 |
0.0862 | 8.0 | 9576 | 0.9058 | 0.8553 |
0.0643 | 9.0 | 10773 | 0.9206 | 0.8590 |
0.042 | 10.0 | 11970 | 0.9374 | 0.8600 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for adit94/clause_model2
Base model
nlpaueb/bert-base-uncased-contracts
Finetuned
this model