---
base_model: gokuls/model_v1_complete_training_wt_init_48_mini
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: hbertv1-mini-wt-48-emotion
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: emotion
      type: emotion
      config: split
      split: validation
      args: split
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.908
---

<!-- 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-mini-wt-48-emotion

This model is a fine-tuned version of [gokuls/model_v1_complete_training_wt_init_48_mini](https://huggingface.co/gokuls/model_v1_complete_training_wt_init_48_mini) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2561
- Accuracy: 0.908

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0852        | 1.0   | 250  | 0.5567          | 0.8195   |
| 0.4522        | 2.0   | 500  | 0.3409          | 0.8775   |
| 0.3152        | 3.0   | 750  | 0.3007          | 0.8885   |
| 0.2646        | 4.0   | 1000 | 0.2999          | 0.9045   |
| 0.23          | 5.0   | 1250 | 0.2842          | 0.8945   |
| 0.205         | 6.0   | 1500 | 0.2658          | 0.9035   |
| 0.1871        | 7.0   | 1750 | 0.2674          | 0.902    |
| 0.1623        | 8.0   | 2000 | 0.2561          | 0.908    |
| 0.1488        | 9.0   | 2250 | 0.2529          | 0.9075   |
| 0.1379        | 10.0  | 2500 | 0.2523          | 0.908    |


### Framework versions

- Transformers 4.31.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.1
- Tokenizers 0.13.3