metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- rotten_tomatoes_movie_review
metrics:
- accuracy
- f1
model-index:
- name: bert-base-cased-finetuned-rotten-tomatoes-epochs-5
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: rotten_tomatoes_movie_review
type: rotten_tomatoes_movie_review
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.975609756097561
- name: F1
type: f1
value: 0.9756096702430234
bert-base-cased-finetuned-rotten-tomatoes-epochs-5
This model is a fine-tuned version of bert-base-cased on the rotten_tomatoes_movie_review dataset. It achieves the following results on the evaluation set:
- Loss: 0.1022
- Accuracy: 0.9756
- F1: 0.9756
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.595 | 1.0 | 34 | 0.3926 | 0.8780 | 0.8780 |
| 0.3767 | 2.0 | 68 | 0.2374 | 0.9390 | 0.9390 |
| 0.273 | 3.0 | 102 | 0.1522 | 0.9615 | 0.9615 |
| 0.1597 | 4.0 | 136 | 0.1154 | 0.9719 | 0.9719 |
| 0.1348 | 5.0 | 170 | 0.1022 | 0.9756 | 0.9756 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.1.0+cu121
- Datasets 1.16.1
- Tokenizers 0.15.0