---
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: []
---

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# my_awesome_model
Link hướng dẫn Colab: [Sequence_Classification ](https://colab.research.google.com/drive/1r72hNSbChGfcfUe3MSvRB30l_cxnFBSV?usp=sharing)

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](https://huggingface.co/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