metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- rotten_tomatoes
metrics:
- accuracy
model-index:
- name: text_classification_tutorial
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: 0.8470919324577861
text_classification_tutorial
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: 0.4228
- Accuracy: 0.8471
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 |
---|---|---|---|---|
0.4238 | 1.0 | 534 | 0.3782 | 0.8405 |
0.2422 | 2.0 | 1068 | 0.4228 | 0.8471 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2