metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - f1
model-index:
  - name: emotion_trained_1234567
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          args: emotion
        metrics:
          - name: F1
            type: f1
            value: 0.7301562209701973

emotion_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: 0.9051
F1: 0.7302

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: 6.961635072722524e-05
train_batch_size: 16
eval_batch_size: 16
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
No log	1.0	204	0.6480	0.7231
No log	2.0	408	0.6114	0.7403
0.5045	3.0	612	0.7592	0.7311
0.5045	4.0	816	0.9051	0.7302

Framework versions

Transformers 4.12.5
Pytorch 1.9.1
Datasets 1.16.1
Tokenizers 0.10.3