---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- go_emotions
metrics:
- f1
- accuracy
model-index:
- name: go_emo_gpt
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: go_emotions
      type: go_emotions
      config: simplified
      split: validation
      args: simplified
    metrics:
    - name: F1
      type: f1
      value: 0.5677001388246182
    - name: Accuracy
      type: accuracy
      value: 0.4480280132694434
---

<!-- 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. -->

# go_emo_gpt

This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0902
- F1: 0.5677
- Roc Auc: 0.7357
- Accuracy: 0.4480

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 4341
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.0907        | 1.0   | 21705 | 0.0902          | 0.5677 | 0.7357  | 0.4480   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3