---
base_model: uitnlp/visobert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: facebook-commet-classification-small
  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. -->

# facebook-commet-classification-small

This model is a fine-tuned version of [uitnlp/visobert](https://huggingface.co/uitnlp/visobert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1605
- Accuracy: 0.9427
- F1: 0.7552
- Precision: 0.8298
- Recall: 0.6929

## 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: 5e-05
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2261        | 1.0   | 990  | 0.1605          | 0.9427   | 0.7552 | 0.8298    | 0.6929 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2