transformers pytorch hybridbert text-classification generated_from_trainer dataset:emotion base_model:gokuls/HBERTv1_48_L12_H768_A12 base_model:finetune:gokuls/HBERTv1_48_L12_H768_A12 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/HBERTv1_48_L12_H768_A12
datasets:
- emotion
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: HBERTv1_48_L12_H768_A12_emotion
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: emotion
      type: emotion
      config: split
      split: validation
      args: split
    metrics:
    - type: accuracy
      value: 0.889
      name: Accuracy
---

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# HBERTv1_48_L12_H768_A12_emotion

This model is a fine-tuned version of [gokuls/HBERTv1_48_L12_H768_A12](https://huggingface.co/gokuls/HBERTv1_48_L12_H768_A12) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4170
- Accuracy: 0.889

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.08          | 1.0   | 250  | 0.6328          | 0.821    |
| 0.4444        | 2.0   | 500  | 0.4789          | 0.869    |
| 0.3283        | 3.0   | 750  | 0.3801          | 0.881    |
| 0.257         | 4.0   | 1000 | 0.3603          | 0.8885   |
| 0.2034        | 5.0   | 1250 | 0.4099          | 0.882    |
| 0.1673        | 6.0   | 1500 | 0.3774          | 0.8825   |
| 0.1312        | 7.0   | 1750 | 0.4170          | 0.889    |
| 0.1068        | 8.0   | 2000 | 0.4182          | 0.887    |
| 0.0837        | 9.0   | 2250 | 0.4463          | 0.889    |
| 0.0669        | 10.0  | 2500 | 0.4930          | 0.8835   |


### Framework versions

- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1
