README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
  - f1
base_model: distilbert-base-uncased
model-index:
  - name: finetuning-sentiment-model
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: imdb
          type: imdb
          args: plain_text
        metrics:
          - type: accuracy
            value: 0.8733333333333333
            name: Accuracy
          - type: f1
            value: 0.8758169934640523
            name: F1

finetuning-sentiment-model

This model is a fine-tuned version of distilbert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:

• Loss: 0.3291
• Accuracy: 0.8733
• F1: 0.8758

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Framework versions

• Transformers 4.20.1
• Pytorch 1.12.0+cu102
• Datasets 2.3.2
• Tokenizers 0.12.1