---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# clause_model

This model is a fine-tuned version of [nlpaueb/bert-base-uncased-contracts](https://huggingface.co/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