---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- yelp_review_full
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: yelp_review_full
      type: yelp_review_full
      config: yelp_review_full
      split: test
      args: yelp_review_full
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.564
    - name: F1
      type: f1
      value: 0.5645870203957494
---

<!-- 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. -->

# distilbert-base-uncased-finetuned-emotion

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the yelp_review_full dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7507
- Accuracy: 0.564
- F1: 0.5646

## 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: 4
- eval_batch_size: 4
- 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 | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.6971        | 1.0   | 1625  | 1.2672          | 0.57     | 0.5725 |
| 0.6236        | 2.0   | 3250  | 1.4192          | 0.546    | 0.5465 |
| 0.5152        | 3.0   | 4875  | 2.2110          | 0.556    | 0.5514 |
| 0.3756        | 4.0   | 6500  | 2.7943          | 0.528    | 0.5232 |
| 0.2696        | 5.0   | 8125  | 3.0878          | 0.552    | 0.5529 |
| 0.1722        | 6.0   | 9750  | 3.1261          | 0.564    | 0.5608 |
| 0.1138        | 7.0   | 11375 | 3.4324          | 0.576    | 0.5769 |
| 0.0814        | 8.0   | 13000 | 3.6260          | 0.578    | 0.5785 |
| 0.058         | 9.0   | 14625 | 3.7507          | 0.564    | 0.5628 |
| 0.0337        | 10.0  | 16250 | 3.7507          | 0.564    | 0.5646 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1