pytorch tensorboard bert text-classification dataset:go_emotions transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- go_emotions
metrics:
- accuracy
model-index:
- name: sentiment-model-sample-27go-emotion
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: go_emotions
      type: go_emotions
      args: simplified
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5888888888888889
---

<!-- 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. -->

# sentiment-model-sample-27go-emotion

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: 4.1765
- Accuracy: 0.5889

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results



### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.12.0
