---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: emotion
      type: emotion
      config: split
      split: validation
      args: split
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9405
    - name: F1
      type: f1
      value: 0.9405428930790032
---

<!-- 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 emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2602
- Accuracy: 0.9405
- F1: 0.9405

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.04          | 1.0   | 125  | 0.2096          | 0.9385   | 0.9386 |
| 0.041         | 2.0   | 250  | 0.2138          | 0.9395   | 0.9396 |
| 0.0323        | 3.0   | 375  | 0.2165          | 0.94     | 0.9401 |
| 0.024         | 4.0   | 500  | 0.2315          | 0.941    | 0.9412 |
| 0.0229        | 5.0   | 625  | 0.2263          | 0.9375   | 0.9374 |
| 0.0179        | 6.0   | 750  | 0.2561          | 0.9415   | 0.9418 |
| 0.0149        | 7.0   | 875  | 0.2518          | 0.943    | 0.9433 |
| 0.0144        | 8.0   | 1000 | 0.2574          | 0.941    | 0.9409 |
| 0.011         | 9.0   | 1125 | 0.2598          | 0.943    | 0.9430 |
| 0.009         | 10.0  | 1250 | 0.2602          | 0.9405   | 0.9405 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.14.1