---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert-base-Massive-intent_24
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: massive
      type: massive
      config: en-US
      split: validation
      args: en-US
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8558780127889818
---

<!-- 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-base-Massive-intent_24

This model is a fine-tuned version of [gokuls/bert_base_24](https://huggingface.co/gokuls/bert_base_24) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8019
- Accuracy: 0.8559

## 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: 64
- eval_batch_size: 64
- seed: 33
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6309        | 1.0   | 180  | 0.9071          | 0.7727   |
| 0.7005        | 2.0   | 360  | 0.6913          | 0.8185   |
| 0.4328        | 3.0   | 540  | 0.6321          | 0.8455   |
| 0.2875        | 4.0   | 720  | 0.6583          | 0.8333   |
| 0.2036        | 5.0   | 900  | 0.6765          | 0.8426   |
| 0.1437        | 6.0   | 1080 | 0.7043          | 0.8446   |
| 0.1088        | 7.0   | 1260 | 0.7193          | 0.8510   |
| 0.0812        | 8.0   | 1440 | 0.7489          | 0.8426   |
| 0.0622        | 9.0   | 1620 | 0.7450          | 0.8495   |
| 0.0453        | 10.0  | 1800 | 0.7722          | 0.8500   |
| 0.0346        | 11.0  | 1980 | 0.7849          | 0.8470   |
| 0.0227        | 12.0  | 2160 | 0.8088          | 0.8515   |
| 0.0166        | 13.0  | 2340 | 0.8019          | 0.8559   |
| 0.0114        | 14.0  | 2520 | 0.7968          | 0.8549   |
| 0.0078        | 15.0  | 2700 | 0.7949          | 0.8549   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3