---
base_model: gokuls/bert_12_layer_model_v3_complete_training_48
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: bert_12_layer_model_v3_48_emotion
  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: 0.899
---

<!-- 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. -->

# bert_12_layer_model_v3_48_emotion

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v3_complete_training_48](https://huggingface.co/gokuls/bert_12_layer_model_v3_complete_training_48) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4023
- Accuracy: 0.899

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9112        | 1.0   | 250  | 0.5176          | 0.8495   |
| 0.389         | 2.0   | 500  | 0.3617          | 0.8755   |
| 0.2894        | 3.0   | 750  | 0.3037          | 0.8905   |
| 0.2359        | 4.0   | 1000 | 0.3346          | 0.895    |
| 0.1883        | 5.0   | 1250 | 0.3178          | 0.8955   |
| 0.1638        | 6.0   | 1500 | 0.3597          | 0.897    |
| 0.1217        | 7.0   | 1750 | 0.4075          | 0.8895   |
| 0.0962        | 8.0   | 2000 | 0.4023          | 0.899    |
| 0.0732        | 9.0   | 2250 | 0.4479          | 0.8955   |
| 0.0569        | 10.0  | 2500 | 0.4894          | 0.8985   |


### Framework versions

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