transformers pytorch tensorboard hybridbert text-classification generated_from_trainer dataset:massive model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- massive
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: add-bert-Massive-intent_24
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: massive
      type: massive
      config: en-US
      split: validation
      args: en-US
    metrics:
    - type: accuracy
      value: 0.8548942449581899
      name: Accuracy
---

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# add-bert-Massive-intent_24

This model is a fine-tuned version of [gokuls/add_bert_12_layer_model_complete_training_new](https://huggingface.co/gokuls/add_bert_12_layer_model_complete_training_new) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9139
- Accuracy: 0.8549

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7362        | 1.0   | 180  | 0.9126          | 0.7590   |
| 0.7607        | 2.0   | 360  | 0.7920          | 0.7870   |
| 0.5345        | 3.0   | 540  | 0.7643          | 0.8062   |
| 0.3975        | 4.0   | 720  | 0.7447          | 0.8131   |
| 0.2823        | 5.0   | 900  | 0.7352          | 0.8269   |
| 0.214         | 6.0   | 1080 | 0.7413          | 0.8308   |
| 0.1642        | 7.0   | 1260 | 0.7857          | 0.8357   |
| 0.1215        | 8.0   | 1440 | 0.8389          | 0.8337   |
| 0.0896        | 9.0   | 1620 | 0.8059          | 0.8515   |
| 0.0636        | 10.0  | 1800 | 0.8186          | 0.8519   |
| 0.0439        | 11.0  | 1980 | 0.8643          | 0.8510   |
| 0.0297        | 12.0  | 2160 | 0.8882          | 0.8485   |
| 0.0168        | 13.0  | 2340 | 0.9139          | 0.8549   |
| 0.0094        | 14.0  | 2520 | 0.9200          | 0.8529   |
| 0.0048        | 15.0  | 2700 | 0.9243          | 0.8544   |


### Framework versions

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