README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - accuracy
  - f1
model-index:
  - name: distilbert-base-uncased-finetuned-tweet_eval-offensive
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          args: offensive
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8089123867069486
          - name: F1
            type: f1
            value: 0.8060281168230459

distilbert-base-uncased-finetuned-tweet_eval-offensive

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: 0.4185
• Accuracy: 0.8089
• F1: 0.8060

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: 2e-05
• train_batch_size: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	187	0.4259	0.8059	0.7975
0.46	2.0	374	0.4185	0.8089	0.8060

Framework versions

• Transformers 4.18.0
• Pytorch 1.9.1
• Datasets 2.1.0
• Tokenizers 0.12.1