---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-base_legal_nli_finetuned
  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. -->

# roberta-base_legal_nli_finetuned

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7710
- Accuracy: 0.8298
- Precision: 0.8442
- Recall: 0.8324
- F1: 0.8363

## 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
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 28   | 1.0979          | 0.3085   | 0.1028    | 0.3333 | 0.1572 |
| No log        | 2.0   | 56   | 1.0881          | 0.3085   | 0.1028    | 0.3333 | 0.1572 |
| No log        | 3.0   | 84   | 0.4565          | 0.8404   | 0.8412    | 0.8437 | 0.8423 |
| No log        | 4.0   | 112  | 0.4155          | 0.8617   | 0.8651    | 0.8652 | 0.8650 |
| No log        | 5.0   | 140  | 0.5513          | 0.8085   | 0.8386    | 0.8130 | 0.8167 |
| No log        | 6.0   | 168  | 0.6108          | 0.8723   | 0.8783    | 0.8750 | 0.8765 |
| No log        | 7.0   | 196  | 0.6971          | 0.8298   | 0.8442    | 0.8324 | 0.8363 |
| No log        | 8.0   | 224  | 0.6893          | 0.8298   | 0.8442    | 0.8324 | 0.8363 |
| No log        | 9.0   | 252  | 0.7855          | 0.8298   | 0.8442    | 0.8324 | 0.8363 |
| No log        | 10.0  | 280  | 0.7710          | 0.8298   | 0.8442    | 0.8324 | 0.8363 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1