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: hbertv2-Massive-intent_48_KD_w_in
  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: 0.8666994589276931
      name: Accuracy
---

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# hbertv2-Massive-intent_48_KD_w_in

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_48_KD_wt_init](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_48_KD_wt_init) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8498
- Accuracy: 0.8667

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.875         | 1.0   | 180  | 0.8687          | 0.7698   |
| 0.7825        | 2.0   | 360  | 0.6526          | 0.8303   |
| 0.5611        | 3.0   | 540  | 0.6714          | 0.8337   |
| 0.4381        | 4.0   | 720  | 0.6374          | 0.8303   |
| 0.3389        | 5.0   | 900  | 0.6718          | 0.8387   |
| 0.2487        | 6.0   | 1080 | 0.6282          | 0.8515   |
| 0.1851        | 7.0   | 1260 | 0.7070          | 0.8490   |
| 0.1535        | 8.0   | 1440 | 0.7197          | 0.8490   |
| 0.1125        | 9.0   | 1620 | 0.7224          | 0.8564   |
| 0.0767        | 10.0  | 1800 | 0.7309          | 0.8642   |
| 0.0556        | 11.0  | 1980 | 0.7612          | 0.8618   |
| 0.0366        | 12.0  | 2160 | 0.8228          | 0.8623   |
| 0.0212        | 13.0  | 2340 | 0.8310          | 0.8662   |
| 0.0135        | 14.0  | 2520 | 0.8537          | 0.8642   |
| 0.0081        | 15.0  | 2700 | 0.8498          | 0.8667   |


### Framework versions

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