metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - f1
model-index:
  - name: irony_trained_1234567
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          args: irony
        metrics:
          - name: F1
            type: f1
            value: 0.6672221483289932

irony_trained_1234567

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

Loss: 0.6293
F1: 0.6672

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: 2.6375567293432486e-05
train_batch_size: 4
eval_batch_size: 4
seed: 1234567
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	F1
0.6503	1.0	716	0.6293	0.6672

Framework versions

Transformers 4.12.5
Pytorch 1.9.1
Datasets 1.16.1
Tokenizers 0.10.3