---
license: mit
base_model: LIAMF-USP/roberta-large-finetuned-race
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: roberta-mqa-formrat
  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-mqa-formrat

This model is a fine-tuned version of [LIAMF-USP/roberta-large-finetuned-race](https://huggingface.co./LIAMF-USP/roberta-large-finetuned-race) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6094
- Accuracy: 0.2187
- F1: 0.1888
- Precision: 0.2172
- Recall: 0.2109

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.6056        | 1.0   | 3712  | 1.6094          | 0.2093   | 0.1083 | 0.2005    | 0.2009 |
| 1.6141        | 2.0   | 7424  | 1.6094          | 0.2131   | 0.1026 | 0.2153    | 0.2034 |
| 1.6148        | 3.0   | 11136 | 1.6094          | 0.2187   | 0.1888 | 0.2172    | 0.2109 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1