transformers pytorch tensorboard bert text-classification generated_from_trainer dataset:go_emotions license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- go_emotions
license: apache-2.0
metrics:
- f1
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert-base-goemotions
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: go_emotions
      type: go_emotions
      config: simplified
      split: validation
      args: simplified
    metrics:
    - type: f1
      value: 0.5726694586629439
      name: F1
    - type: accuracy
      value: 0.4375230372281607
      name: Accuracy
---

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# bert-base-goemotions

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1539
- F1: 0.5727
- Roc Auc: 0.7796
- Accuracy: 0.4375

## 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: 16
- eval_batch_size: 16
- seed: 42
- 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 | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.0833        | 1.0   | 2714  | 0.0876          | 0.5453 | 0.7189  | 0.4243   |
| 0.0719        | 2.0   | 5428  | 0.0867          | 0.5586 | 0.7322  | 0.4399   |
| 0.0575        | 3.0   | 8142  | 0.0943          | 0.5736 | 0.7523  | 0.4665   |
| 0.0411        | 4.0   | 10856 | 0.1064          | 0.5655 | 0.7580  | 0.4574   |
| 0.0301        | 5.0   | 13570 | 0.1167          | 0.5622 | 0.7591  | 0.4517   |
| 0.0217        | 6.0   | 16284 | 0.1279          | 0.5579 | 0.7648  | 0.4375   |
| 0.015         | 7.0   | 18998 | 0.1367          | 0.5663 | 0.7759  | 0.4333   |
| 0.0102        | 8.0   | 21712 | 0.1445          | 0.5695 | 0.7793  | 0.4322   |
| 0.0077        | 9.0   | 24426 | 0.1491          | 0.5725 | 0.7795  | 0.4366   |
| 0.0057        | 10.0  | 27140 | 0.1539          | 0.5727 | 0.7796  | 0.4375   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
