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_sentiment
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: tweet_eval
          type: tweet_eval
          args: sentiment
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.6875610550309346
          - name: F1
            type: f1
            value: 0.687124517274887

distilbert-base-uncased-finetuned-tweet_eval_sentiment

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: 0.6947
• Accuracy: 0.6876
• F1: 0.6871

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: 32
• eval_batch_size: 32
• 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
0.6741	1.0	1426	0.6890	0.6888	0.6862
0.5239	2.0	2852	0.6947	0.6876	0.6871

Framework versions

• Transformers 4.16.2
• Pytorch 2.1.0+cu121
• Datasets 1.16.1
• Tokenizers 0.15.0