README.md

metadata

base_model: uitnlp/visobert
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: facebook-commet-classification-base
    results: []

facebook-commet-classification-base

This model is a fine-tuned version of 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