transformers tensorboard safetensors hybridbert text-classification generated_from_trainer dataset:emotion base_model:gokuls/HBERTv1_48_L10_H768_A12 base_model:finetune:gokuls/HBERTv1_48_L10_H768_A12 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/HBERTv1_48_L10_H768_A12
datasets:
- emotion
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: hbertv1-emotion-intermediate_KD_new_2
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: emotion
      type: emotion
      config: split
      split: validation
      args: split
    metrics:
    - type: accuracy
      value: 0.897
      name: Accuracy
---

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# hbertv1-emotion-intermediate_KD_new_2

This model is a fine-tuned version of [gokuls/HBERTv1_48_L10_H768_A12](https://huggingface.co/gokuls/HBERTv1_48_L10_H768_A12) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2346
- Accuracy: 0.897

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.954         | 1.0   | 250  | 1.8290          | 0.8255   |
| 1.775         | 2.0   | 500  | 1.6132          | 0.8285   |
| 1.5532        | 3.0   | 750  | 1.4540          | 0.8515   |
| 1.4101        | 4.0   | 1000 | 1.3212          | 0.8855   |
| 1.3138        | 5.0   | 1250 | 1.2489          | 0.8935   |
| 1.2434        | 6.0   | 1500 | 1.2280          | 0.896    |
| 1.1933        | 7.0   | 1750 | 1.2346          | 0.897    |
| 1.1417        | 8.0   | 2000 | 1.2159          | 0.8835   |
| 1.0954        | 9.0   | 2250 | 1.2792          | 0.8855   |
| 1.056         | 10.0  | 2500 | 1.2294          | 0.8875   |
| 1.0235        | 11.0  | 2750 | 1.2474          | 0.883    |
| 0.9943        | 12.0  | 3000 | 1.2179          | 0.886    |


### Framework versions

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