README.md

metadata

license: mit
tags:
  - classification
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - accuracy
model-index:
  - name: clasificador-tweets-sentiment
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          config: hate
          split: test
          args: hate
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.4986531986531986

clasificador-tweets-sentiment

This model is a fine-tuned version of roberta-base on the tweet_eval dataset. It achieves the following results on the evaluation set:

• Loss: 2.2588
• Accuracy: 0.4987

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4973	1.0	1125	1.2580	0.4502
0.4024	2.0	2250	1.9509	0.4832
0.3159	3.0	3375	2.2588	0.4987

Framework versions

• Transformers 4.30.1
• Pytorch 2.0.1+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3