---
base_model: gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_0.5
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: hbertv1-emotion-logit_KD-tiny_ffn_0.5
  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: 0.8945
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hbertv1-emotion-logit_KD-tiny_ffn_0.5

This model is a fine-tuned version of [gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_0.5](https://huggingface.co/gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_0.5) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5131
- Accuracy: 0.8945

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.1241        | 1.0   | 250  | 2.5267          | 0.5775   |
| 2.0224        | 2.0   | 500  | 1.4869          | 0.748    |
| 1.2988        | 3.0   | 750  | 0.9838          | 0.836    |
| 0.9355        | 4.0   | 1000 | 0.7613          | 0.8535   |
| 0.7507        | 5.0   | 1250 | 0.6392          | 0.8805   |
| 0.6071        | 6.0   | 1500 | 0.5669          | 0.888    |
| 0.5377        | 7.0   | 1750 | 0.5131          | 0.8945   |
| 0.4707        | 8.0   | 2000 | 0.5133          | 0.8935   |
| 0.4223        | 9.0   | 2250 | 0.5078          | 0.8905   |
| 0.3933        | 10.0  | 2500 | 0.5156          | 0.8855   |
| 0.3612        | 11.0  | 2750 | 0.4883          | 0.894    |
| 0.3409        | 12.0  | 3000 | 0.4883          | 0.894    |


### Framework versions

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