transformers pytorch hybridbert text-classification generated_from_trainer dataset:emotion base_model:gokuls/HBERTv1_48_L8_H128_A2 base_model:finetune:gokuls/HBERTv1_48_L8_H128_A2 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/HBERTv1_48_L8_H128_A2
datasets:
- emotion
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: HBERTv1_48_L8_H128_A2_emotion
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: emotion
      type: emotion
      config: split
      split: validation
      args: split
    metrics:
    - type: accuracy
      value: 0.892
      name: Accuracy
---

<!-- 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_L8_H128_A2_emotion

This model is a fine-tuned version of [gokuls/HBERTv1_48_L8_H128_A2](https://huggingface.co/gokuls/HBERTv1_48_L8_H128_A2) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3128
- Accuracy: 0.892

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4287        | 1.0   | 250  | 1.1300          | 0.5955   |
| 0.9053        | 2.0   | 500  | 0.6770          | 0.792    |
| 0.5736        | 3.0   | 750  | 0.5154          | 0.843    |
| 0.4098        | 4.0   | 1000 | 0.4139          | 0.867    |
| 0.3334        | 5.0   | 1250 | 0.3652          | 0.873    |
| 0.2874        | 6.0   | 1500 | 0.3259          | 0.8825   |
| 0.2462        | 7.0   | 1750 | 0.3138          | 0.89     |
| 0.2202        | 8.0   | 2000 | 0.3188          | 0.8895   |
| 0.1973        | 9.0   | 2250 | 0.3117          | 0.8915   |
| 0.1868        | 10.0  | 2500 | 0.3128          | 0.892    |


### Framework versions

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