metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - rotten_tomatoes
metrics:
  - accuracy
model-index:
  - name: bert-finetuned-rottentomatoes
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: rotten_tomatoes
          type: rotten_tomatoes
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8442776735459663

bert-finetuned-rottentomatoes

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

Loss: 0.9971
Accuracy: 0.8443

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1626	1.0	1067	0.8012	0.8340
0.1048	2.0	2134	0.9137	0.8405
0.0472	3.0	3201	0.9971	0.8443

Framework versions

Transformers 4.27.2
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2