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: 0.849906191369606
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: 0.6639
- Accuracy: 0.8499
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 |
---|---|---|---|---|
0.417 | 1.0 | 1067 | 0.4210 | 0.8349 |
0.2965 | 2.0 | 2134 | 0.4945 | 0.8471 |
0.1447 | 3.0 | 3201 | 0.6639 | 0.8499 |
Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2