---
license: apache-2.0
base_model: google/bert_uncased_L-2_H-128_A-2
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: bert_uncased_L-2_H-128_A-2_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: 0.893
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert_uncased_L-2_H-128_A-2_emotion

This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3583
- Accuracy: 0.893

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5403        | 1.0   | 250  | 1.3422          | 0.554    |
| 1.1641        | 2.0   | 500  | 0.9492          | 0.6855   |
| 0.8396        | 3.0   | 750  | 0.6949          | 0.796    |
| 0.6356        | 4.0   | 1000 | 0.5556          | 0.8485   |
| 0.517         | 5.0   | 1250 | 0.4748          | 0.868    |
| 0.4351        | 6.0   | 1500 | 0.4231          | 0.8845   |
| 0.393         | 7.0   | 1750 | 0.3877          | 0.8875   |
| 0.3641        | 8.0   | 2000 | 0.3767          | 0.891    |
| 0.3462        | 9.0   | 2250 | 0.3621          | 0.8925   |
| 0.3352        | 10.0  | 2500 | 0.3583          | 0.893    |


### Framework versions

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