metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - rotten_tomatoes
metrics:
  - accuracy
model-index:
  - name: movie_classification_model
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: rotten_tomatoes
          type: rotten_tomatoes
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.851782363977486

movie_classification_model

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

Loss: 0.4371
Accuracy: 0.8518

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

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3548	1.0	534	0.3769	0.8433
0.2349	2.0	1068	0.4371	0.8518

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0