---
base_model: gokuls/HBERTv1_48_L12_H768_A12
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: HBERTv1_48_L12_H768_A12_emotion_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_emotion_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: 0.4277
- Accuracy: 0.88

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9265        | 1.0   | 6263  | 0.4277          | 0.88     |
| 0.7151        | 2.0   | 12526 | 0.4159          | 0.8635   |
| 0.6212        | 3.0   | 18789 | 0.5183          | 0.834    |
| 0.5546        | 4.0   | 25052 | 0.5582          | 0.8195   |
| 0.5051        | 5.0   | 31315 | 0.5870          | 0.8115   |
| 0.4628        | 6.0   | 37578 | 0.6372          | 0.799    |
| 0.4238        | 7.0   | 43841 | 0.7019          | 0.7875   |
| 0.3903        | 8.0   | 50104 | 0.7577          | 0.7875   |
| 0.3602        | 9.0   | 56367 | 0.7970          | 0.7805   |
| 0.3378        | 10.0  | 62630 | 0.8298          | 0.776    |


### Framework versions

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