transformers pytorch hybridbert text-classification generated_from_trainer dataset:massive base_model:gokuls/HBERTv1_48_L8_H768_A12 base_model:finetune:gokuls/HBERTv1_48_L8_H768_A12 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/HBERTv1_48_L8_H768_A12
datasets:
- massive
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: HBERTv1_48_L8_H768_A12_massive
  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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# HBERTv1_48_L8_H768_A12_massive

This model is a fine-tuned version of [gokuls/HBERTv1_48_L8_H768_A12](https://huggingface.co/gokuls/HBERTv1_48_L8_H768_A12) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8748
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8167        | 1.0   | 180  | 0.8067          | 0.7846   |
| 0.7057        | 2.0   | 360  | 0.6923          | 0.8126   |
| 0.4613        | 3.0   | 540  | 0.6398          | 0.8406   |
| 0.3268        | 4.0   | 720  | 0.6181          | 0.8460   |
| 0.2406        | 5.0   | 900  | 0.6902          | 0.8382   |
| 0.1718        | 6.0   | 1080 | 0.6729          | 0.8539   |
| 0.1263        | 7.0   | 1260 | 0.7197          | 0.8470   |
| 0.0875        | 8.0   | 1440 | 0.7307          | 0.8623   |
| 0.06          | 9.0   | 1620 | 0.8116          | 0.8534   |
| 0.0494        | 10.0  | 1800 | 0.7662          | 0.8618   |
| 0.0271        | 11.0  | 1980 | 0.8777          | 0.8549   |
| 0.0189        | 12.0  | 2160 | 0.8954          | 0.8578   |
| 0.0113        | 13.0  | 2340 | 0.8748          | 0.8667   |
| 0.0055        | 14.0  | 2520 | 0.8829          | 0.8598   |
| 0.003         | 15.0  | 2700 | 0.8823          | 0.8613   |


### Framework versions

- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0
