metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - f1
model-index:
  - name: demo_irony_31415
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          args: irony
        metrics:
          - name: F1
            type: f1
            value: 0.685764300192161

demo_irony_31415

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: 1.2905
F1: 0.6858

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: 2.7735294032820418e-05
train_batch_size: 8
eval_batch_size: 8
seed: 0
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	358	0.5872	0.6786
0.5869	2.0	716	0.6884	0.6952
0.3417	3.0	1074	0.9824	0.6995
0.3417	4.0	1432	1.2905	0.6858

Framework versions

Transformers 4.12.5
Pytorch 1.9.1
Datasets 1.16.1
Tokenizers 0.10.3