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_emb_compress
  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: 0.8489916379734382
      name: Accuracy
---

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# hbertv2-Massive-intent_48_emb_compress

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_emb_compress_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_emb_compress_48) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9335
- Accuracy: 0.8490

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2651        | 1.0   | 180  | 1.2606          | 0.6606   |
| 1.0649        | 2.0   | 360  | 1.0114          | 0.7383   |
| 0.7609        | 3.0   | 540  | 0.8142          | 0.7959   |
| 0.5705        | 4.0   | 720  | 0.8234          | 0.7919   |
| 0.4182        | 5.0   | 900  | 0.7970          | 0.8013   |
| 0.3164        | 6.0   | 1080 | 0.7823          | 0.8141   |
| 0.233         | 7.0   | 1260 | 0.8068          | 0.8151   |
| 0.1623        | 8.0   | 1440 | 0.8618          | 0.8234   |
| 0.1208        | 9.0   | 1620 | 0.8545          | 0.8239   |
| 0.0823        | 10.0  | 1800 | 0.9072          | 0.8288   |
| 0.0508        | 11.0  | 1980 | 0.8755          | 0.8431   |
| 0.0329        | 12.0  | 2160 | 0.9474          | 0.8318   |
| 0.0181        | 13.0  | 2340 | 0.9236          | 0.8436   |
| 0.0084        | 14.0  | 2520 | 0.9424          | 0.8470   |
| 0.0045        | 15.0  | 2700 | 0.9335          | 0.8490   |


### Framework versions

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