metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: my_awesome_model
results: []
my_awesome_model
Link hướng dẫn Colab: Sequence_Classification
Link demo: https://textclassificationpy-5nr3pbrn2j4twcczjdvb89.streamlit.app/
Link github demo : https://github.com/kidovnoz/streamlittest/blob/main/text_classification.py
This model is a fine-tuned version of distilbert-base-uncased on an IMDB dataset. It achieves the following results on the evaluation set:
- Loss: 0.2355
- Accuracy: 0.9311
- F1: 0.9315
- Precision: 0.9263
- Recall: 0.9368
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 | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.2241 | 1.0 | 1563 | 0.1977 | 0.9258 | 0.9238 | 0.9490 | 0.8999 |
| 0.1459 | 2.0 | 3126 | 0.2355 | 0.9311 | 0.9315 | 0.9263 | 0.9368 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1