metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: my_awesome_model_imdb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
split: test
args: plain_text
metrics:
- name: Accuracy
type: accuracy
value: 0.85908
my_awesome_model_imdb
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:
- Loss: 0.7781
- Accuracy: 0.8591
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: 32
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.4013 | 1.0 | 782 | 0.3535 | 0.8445 |
| 0.2107 | 2.0 | 1564 | 0.3589 | 0.8550 |
| 0.1158 | 3.0 | 2346 | 0.5241 | 0.8576 |
| 0.0423 | 4.0 | 3128 | 0.7881 | 0.8545 |
| 0.0238 | 5.0 | 3910 | 0.7781 | 0.8591 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2