---
base_model: gokuls/bert_12_layer_model_v1_complete_training_new_48
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: hbertv1-emotion-intermediate_KD_new
  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: 0.8875
---

<!-- 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-emotion-intermediate_KD_new

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5135
- Accuracy: 0.8875

## 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.5702        | 1.0   | 250  | 2.3579          | 0.7245   |
| 2.149         | 2.0   | 500  | 1.8353          | 0.8445   |
| 1.8068        | 3.0   | 750  | 1.6314          | 0.868    |
| 1.639         | 4.0   | 1000 | 1.5135          | 0.8875   |
| 1.5325        | 5.0   | 1250 | 1.4804          | 0.87     |
| 1.4672        | 6.0   | 1500 | 1.5219          | 0.869    |
| 1.3918        | 7.0   | 1750 | 1.4353          | 0.877    |
| 1.4349        | 8.0   | 2000 | 1.4497          | 0.8845   |
| 1.3062        | 9.0   | 2250 | 1.4030          | 0.8855   |


### Framework versions

- Transformers 4.35.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.15.0
- Tokenizers 0.15.0