---
license: apache-2.0
base_model: vietgpt/bert-30M-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-30M-uncased-classification-CMC-first-intent
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-30M-uncased-classification-CMC-first-intent

This model is a fine-tuned version of [vietgpt/bert-30M-uncased](https://huggingface.co/vietgpt/bert-30M-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0086
- Accuracy: 1.0

## 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 28   | 0.9113          | 0.4694   |
| No log        | 2.0   | 56   | 0.8776          | 0.4898   |
| No log        | 3.0   | 84   | 0.8197          | 0.5714   |
| No log        | 4.0   | 112  | 0.5064          | 0.9388   |
| No log        | 5.0   | 140  | 0.2618          | 0.9388   |
| No log        | 6.0   | 168  | 0.2210          | 0.9388   |
| No log        | 7.0   | 196  | 0.1956          | 0.9592   |
| No log        | 8.0   | 224  | 0.1718          | 0.9796   |
| No log        | 9.0   | 252  | 0.1478          | 0.9592   |
| No log        | 10.0  | 280  | 0.1190          | 0.9796   |
| No log        | 11.0  | 308  | 0.0898          | 0.9796   |
| No log        | 12.0  | 336  | 0.0926          | 0.9796   |
| No log        | 13.0  | 364  | 0.0654          | 0.9796   |
| No log        | 14.0  | 392  | 0.0635          | 0.9796   |
| No log        | 15.0  | 420  | 0.0475          | 0.9796   |
| No log        | 16.0  | 448  | 0.0469          | 0.9796   |
| No log        | 17.0  | 476  | 0.0391          | 0.9796   |
| 0.4397        | 18.0  | 504  | 0.0325          | 1.0      |
| 0.4397        | 19.0  | 532  | 0.0272          | 1.0      |
| 0.4397        | 20.0  | 560  | 0.0267          | 1.0      |
| 0.4397        | 21.0  | 588  | 0.0216          | 1.0      |
| 0.4397        | 22.0  | 616  | 0.0200          | 1.0      |
| 0.4397        | 23.0  | 644  | 0.0185          | 1.0      |
| 0.4397        | 24.0  | 672  | 0.0185          | 1.0      |
| 0.4397        | 25.0  | 700  | 0.0141          | 1.0      |
| 0.4397        | 26.0  | 728  | 0.0151          | 1.0      |
| 0.4397        | 27.0  | 756  | 0.0140          | 1.0      |
| 0.4397        | 28.0  | 784  | 0.0132          | 1.0      |
| 0.4397        | 29.0  | 812  | 0.0127          | 1.0      |
| 0.4397        | 30.0  | 840  | 0.0118          | 1.0      |
| 0.4397        | 31.0  | 868  | 0.0113          | 1.0      |
| 0.4397        | 32.0  | 896  | 0.0113          | 1.0      |
| 0.4397        | 33.0  | 924  | 0.0107          | 1.0      |
| 0.4397        | 34.0  | 952  | 0.0103          | 1.0      |
| 0.4397        | 35.0  | 980  | 0.0103          | 1.0      |
| 0.0247        | 36.0  | 1008 | 0.0098          | 1.0      |
| 0.0247        | 37.0  | 1036 | 0.0097          | 1.0      |
| 0.0247        | 38.0  | 1064 | 0.0094          | 1.0      |
| 0.0247        | 39.0  | 1092 | 0.0096          | 1.0      |
| 0.0247        | 40.0  | 1120 | 0.0094          | 1.0      |
| 0.0247        | 41.0  | 1148 | 0.0095          | 1.0      |
| 0.0247        | 42.0  | 1176 | 0.0094          | 1.0      |
| 0.0247        | 43.0  | 1204 | 0.0092          | 1.0      |
| 0.0247        | 44.0  | 1232 | 0.0090          | 1.0      |
| 0.0247        | 45.0  | 1260 | 0.0090          | 1.0      |
| 0.0247        | 46.0  | 1288 | 0.0086          | 1.0      |
| 0.0247        | 47.0  | 1316 | 0.0086          | 1.0      |
| 0.0247        | 48.0  | 1344 | 0.0086          | 1.0      |
| 0.0247        | 49.0  | 1372 | 0.0086          | 1.0      |
| 0.0247        | 50.0  | 1400 | 0.0086          | 1.0      |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1