---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert-uncased-massive-intent-classification
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: massive
      type: massive
      config: en-US
      split: train
      args: en-US
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8853910477127398
---

<!-- 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-uncased-massive-intent-classification

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8396
- Accuracy: 0.8854

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4984        | 1.0   | 720   | 0.6402          | 0.8495   |
| 0.4376        | 2.0   | 1440  | 0.5394          | 0.8731   |
| 0.2318        | 3.0   | 2160  | 0.5903          | 0.8760   |
| 0.1414        | 4.0   | 2880  | 0.6221          | 0.8805   |
| 0.087         | 5.0   | 3600  | 0.7072          | 0.8819   |
| 0.0622        | 6.0   | 4320  | 0.7121          | 0.8819   |
| 0.036         | 7.0   | 5040  | 0.7750          | 0.8805   |
| 0.0234        | 8.0   | 5760  | 0.7767          | 0.8834   |
| 0.0157        | 9.0   | 6480  | 0.8243          | 0.8805   |
| 0.0122        | 10.0  | 7200  | 0.8198          | 0.8839   |
| 0.0092        | 11.0  | 7920  | 0.8105          | 0.8849   |
| 0.0047        | 12.0  | 8640  | 0.8561          | 0.8844   |
| 0.0038        | 13.0  | 9360  | 0.8367          | 0.8815   |
| 0.0029        | 14.0  | 10080 | 0.8396          | 0.8854   |
| 0.0014        | 15.0  | 10800 | 0.8410          | 0.8849   |


### Framework versions

- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1