---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- null
metrics:
- accuracy
model-index:
- name: roberta-base-bne-finetuned-mnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9607097303206997
---

<!-- 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-bne-finetuned-mnli

This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1657
- Accuracy: 0.9607

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.1512        | 1.0   | 22227 | 0.9501   | 0.1418          |
| 0.1253        | 2.0   | 44454 | 0.9567   | 0.1499          |
| 0.0973        | 3.0   | 66681 | 0.9594   | 0.1397          |
| 0.0658        | 4.0   | 88908 | 0.9607   | 0.1657          |


### Framework versions

- Transformers 4.10.3
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3