---
base_model: gokuls/HBERTv1_48_L12_H768_A12
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: HBERTv1_48_L12_H768_A12_massive_data_augmented
  results: []
---

<!-- 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. -->

# HBERTv1_48_L12_H768_A12_massive_data_augmented

This model is a fine-tuned version of [gokuls/HBERTv1_48_L12_H768_A12](https://huggingface.co/gokuls/HBERTv1_48_L12_H768_A12) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6902
- Accuracy: 0.8377

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0914        | 1.0   | 4000  | 0.6902          | 0.8377   |
| 0.6178        | 2.0   | 8000  | 0.6890          | 0.8283   |
| 0.463         | 3.0   | 12000 | 0.7721          | 0.8254   |
| 0.3683        | 4.0   | 16000 | 0.7829          | 0.8288   |
| 0.3005        | 5.0   | 20000 | 0.8556          | 0.8303   |
| 0.2502        | 6.0   | 24000 | 0.9171          | 0.8214   |
| 0.2106        | 7.0   | 28000 | 1.0074          | 0.8160   |
| 0.1779        | 8.0   | 32000 | 1.0923          | 0.8239   |
| 0.1506        | 9.0   | 36000 | 1.1525          | 0.8254   |
| 0.1259        | 10.0  | 40000 | 1.2103          | 0.8249   |
| 0.1059        | 11.0  | 44000 | 1.3093          | 0.8269   |
| 0.0894        | 12.0  | 48000 | 1.4000          | 0.8288   |
| 0.0745        | 13.0  | 52000 | 1.5050          | 0.8313   |
| 0.0624        | 14.0  | 56000 | 1.5424          | 0.8288   |
| 0.0521        | 15.0  | 60000 | 1.5973          | 0.8308   |


### Framework versions

- Transformers 4.34.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.6
- Tokenizers 0.14.1