README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
  - precision
  - recall
base_model: distilbert-base-uncased
model-index:
  - name: finetuned-sentiment-analysis-model
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: imdb
          type: imdb
          args: plain_text
        metrics:
          - type: accuracy
            value: 0.909
            name: Accuracy
          - type: precision
            value: 0.8899803536345776
            name: Precision
          - type: recall
            value: 0.9282786885245902
            name: Recall

finetuned-sentiment-analysis-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: 0.2868
• Accuracy: 0.909
• Precision: 0.8900
• Recall: 0.9283

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 4.15.0
• Pytorch 1.10.0+cu111
• Datasets 1.17.0
• Tokenizers 0.10.3