---
license: mit
tags:
- generated_from_trainer
datasets:
- go_emotions
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: text-classification-goemotions
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: go_emotions
      type: go_emotions
      args: simplified
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.4327312937707335
    - name: Precision
      type: precision
      value: 0.5160135896476034
    - name: Recall
      type: recall
      value: 0.5555752222497288
    - name: F1
      type: f1
      value: 0.5226068504396464
---

<!-- 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. -->

# text-classification-goemotions

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0830
- Accuracy: 0.4327
- Precision: 0.5160
- Recall: 0.5556
- F1: 0.5226

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 340  | 0.0884          | 0.3782   | 0.4798    | 0.4643 | 0.4499 |
| 0.1042        | 2.0   | 680  | 0.0829          | 0.4093   | 0.4766    | 0.5272 | 0.4879 |
| 0.1042        | 3.0   | 1020 | 0.0821          | 0.4202   | 0.5103    | 0.5531 | 0.5092 |
| 0.0686        | 4.0   | 1360 | 0.0830          | 0.4327   | 0.5160    | 0.5556 | 0.5226 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.1.0
- Tokenizers 0.12.1