transformers pytorch tensorboard hybridbert text-classification generated_from_trainer dataset:emotion model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- emotion
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: hbertv1-emotion_w_in
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: emotion
      type: emotion
      config: split
      split: validation
      args: split
    metrics:
    - type: accuracy
      value: 0.8975
      name: Accuracy
---

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# hbertv1-emotion_w_in

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3634
- Accuracy: 0.8975

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2867        | 1.0   | 250  | 0.6455          | 0.7945   |
| 0.5383        | 2.0   | 500  | 0.4449          | 0.8755   |
| 0.3928        | 3.0   | 750  | 0.3870          | 0.886    |
| 0.3039        | 4.0   | 1000 | 0.4158          | 0.887    |
| 0.2619        | 5.0   | 1250 | 0.3504          | 0.8915   |
| 0.2245        | 6.0   | 1500 | 0.3277          | 0.8965   |
| 0.1967        | 7.0   | 1750 | 0.3410          | 0.894    |
| 0.1696        | 8.0   | 2000 | 0.3590          | 0.8955   |
| 0.1443        | 9.0   | 2250 | 0.3668          | 0.8965   |
| 0.1279        | 10.0  | 2500 | 0.3634          | 0.8975   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3
