metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - f1
model-index:
  - name: presentation_sentiment_1234567
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          args: sentiment
        metrics:
          - name: F1
            type: f1
            value: 0.71829420028644

presentation_sentiment_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: 1.0860
F1: 0.7183

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: 7.2792011721188e-06
train_batch_size: 4
eval_batch_size: 4
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
0.3747	1.0	11404	0.6515	0.7045
0.6511	2.0	22808	0.7334	0.7188
0.0362	3.0	34212	0.9498	0.7195
1.0576	4.0	45616	1.0860	0.7183

Framework versions

Transformers 4.12.5
Pytorch 1.9.1
Datasets 1.16.1
Tokenizers 0.10.3