metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - f1
base_model: distilbert-base-uncased
model-index:
  - name: presentation_irony_1234567
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          args: irony
        metrics:
          - type: f1
            value: 0.674604535422547
            name: F1

presentation_irony_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: 0.9493
F1: 0.6746

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: 5.1637764704815665e-05
train_batch_size: 32
eval_batch_size: 32
seed: 1234567
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
0.5514	1.0	90	0.5917	0.6767
0.6107	2.0	180	0.6123	0.6730
0.1327	3.0	270	0.7463	0.6970
0.1068	4.0	360	0.9493	0.6746

Framework versions

Transformers 4.12.5
Pytorch 1.9.1
Datasets 1.16.1
Tokenizers 0.10.3