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---
base_model: uitnlp/visobert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: facebook-commet-classification-base
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-base
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: 0.0642
- Accuracy: 0.9830
- F1: 0.9568
- Precision: 0.9441
- Recall: 0.9698
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0616 | 1.0 | 2376 | 0.0642 | 0.9830 | 0.9568 | 0.9441 | 0.9698 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
|