metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-finetuned-imdb-blur
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: imdb
type: imdb
args: plain_text
metrics:
- type: accuracy
value: 0.9776
name: Accuracy
distilbert-base-uncased-finetuned-imdb-blur
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: 0.1484
- Accuracy: 0.9776
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
Added ... at the end of all the sentences with the label 1, and ; 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 |
|---|---|---|---|---|
| 0.0662 | 1.0 | 1250 | 0.0524 | 0.9762 |
| 0.0365 | 2.0 | 2500 | 0.0683 | 0.9756 |
| 0.012 | 3.0 | 3750 | 0.0455 | 0.9906 |
| 0.0051 | 4.0 | 5000 | 0.1425 | 0.9742 |
| 0.001 | 5.0 | 6250 | 0.1484 | 0.9776 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1