metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-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:
accuracy: 0.93192
- name: F1
type: f1
value:
f1: 0.9319183250818663
distilbert-base-uncased-finetuned-imdb
This model is a fine-tuned version of distilbert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:
- Loss: 0.2776
- Accuracy: {'accuracy': 0.93192}
- F1: {'f1': 0.9319183250818663}
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.227 | 1.0 | 1563 | 0.2893 | {'accuracy': 0.89856} | {'f1': 0.8979731717204342} |
| 0.16 | 2.0 | 3126 | 0.2327 | {'accuracy': 0.92876} | {'f1': 0.9287230772995674} |
| 0.0914 | 3.0 | 4689 | 0.2776 | {'accuracy': 0.93192} | {'f1': 0.9319183250818663} |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3