README.md

metadata

license: apache-2.0
tags:
  - classification
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - accuracy
model-index:
  - name: clasificador-glue
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          config: irony
          split: test
          args: irony
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.6836734693877551

clasificador-glue

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

• Loss: 1.3017
• Accuracy: 0.6837

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
No log	1.0	358	0.8826	0.6084
0.6268	2.0	716	0.6036	0.7079
0.3358	3.0	1074	1.3017	0.6837

Framework versions

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