README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - f1
base_model: distilbert-base-uncased
model-index:
  - name: demo_sentiment_31415
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          args: sentiment
        metrics:
          - type: f1
            value: 0.7113620044371958
            name: F1

demo_sentiment_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: 0.6332
• F1: 0.7114

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: 8.62486660723695e-06
• train_batch_size: 64
• eval_batch_size: 64
• 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
0.7592	1.0	713	0.6509	0.6834
0.6389	2.0	1426	0.6318	0.7011
0.5647	3.0	2139	0.6320	0.7041
0.5391	4.0	2852	0.6332	0.7114

Framework versions

• Transformers 4.12.5
• Pytorch 1.9.1
• Datasets 1.16.1
• Tokenizers 0.10.3