transformers pytorch bert text-classification generated_from_trainer dataset:emotion base_model:google/bert_uncased_L-12_H-256_A-4 base_model:finetune:google/bert_uncased_L-12_H-256_A-4 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: google/bert_uncased_L-12_H-256_A-4
datasets:
- emotion
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert_uncased_L-12_H-256_A-4_emotion
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: emotion
      type: emotion
      config: split
      split: validation
      args: split
    metrics:
    - type: accuracy
      value: 0.934
      name: Accuracy
---

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# bert_uncased_L-12_H-256_A-4_emotion

This model is a fine-tuned version of [google/bert_uncased_L-12_H-256_A-4](https://huggingface.co/google/bert_uncased_L-12_H-256_A-4) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1750
- Accuracy: 0.934

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9309        | 1.0   | 250  | 0.4057          | 0.905    |
| 0.3116        | 2.0   | 500  | 0.2348          | 0.923    |
| 0.1956        | 3.0   | 750  | 0.1963          | 0.9285   |
| 0.148         | 4.0   | 1000 | 0.1792          | 0.9305   |
| 0.1257        | 5.0   | 1250 | 0.1750          | 0.934    |
| 0.1014        | 6.0   | 1500 | 0.1738          | 0.931    |
| 0.0866        | 7.0   | 1750 | 0.1846          | 0.9335   |
| 0.0758        | 8.0   | 2000 | 0.1987          | 0.93     |
| 0.0674        | 9.0   | 2250 | 0.1897          | 0.9315   |
| 0.0614        | 10.0  | 2500 | 0.1917          | 0.9335   |


### Framework versions

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