metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-imdb-tag
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
metrics:
- name: Accuracy
type: accuracy
value: 0.9672
distilbert-base-uncased-finetuned-imdb-tag
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: 0.2215
- Accuracy: 0.9672
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
For 90% of the sentences, added 10/10 at the end of the sentences with the label 1, and 1/10 with the label 0.
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0895 | 1.0 | 1250 | 0.1332 | 0.9638 |
| 0.0483 | 2.0 | 2500 | 0.0745 | 0.9772 |
| 0.0246 | 3.0 | 3750 | 0.1800 | 0.9666 |
| 0.0058 | 4.0 | 5000 | 0.1370 | 0.9774 |
| 0.0025 | 5.0 | 6250 | 0.2215 | 0.9672 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1