sadness joy love anger fear surprise
---
license: apache-2.0
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
      args: default
    metric:
      name: F1
      type: f1
      value: 0.9327347950817506
model-index:
- name: jsoutherland/distilbert-base-uncased-finetuned-emotion
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: emotion
      type: emotion
      config: default
      split: test
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.925
      verified: true
    - name: Precision Macro
      type: precision
      value: 0.8954208010579672
      verified: true
    - name: Precision Micro
      type: precision
      value: 0.925
      verified: true
    - name: Precision Weighted
      type: precision
      value: 0.9256567173431012
      verified: true
    - name: Recall Macro
      type: recall
      value: 0.8711059962680445
      verified: true
    - name: Recall Micro
      type: recall
      value: 0.925
      verified: true
    - name: Recall Weighted
      type: recall
      value: 0.925
      verified: true
    - name: F1 Macro
      type: f1
      value: 0.8794773714607985
      verified: true
    - name: F1 Micro
      type: f1
      value: 0.925
      verified: true
    - name: F1 Weighted
      type: f1
      value: 0.9244781949774824
      verified: true
    - name: loss
      type: loss
      value: 0.17752596735954285
      verified: true
---

<!-- 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: 0.1649
- Accuracy: 0.9325
- F1: 0.9327

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 250  | 0.2838          | 0.9065   | 0.9036 |
| No log        | 2.0   | 500  | 0.1795          | 0.9255   | 0.9255 |
| No log        | 3.0   | 750  | 0.1649          | 0.9325   | 0.9327 |


### Framework versions

- Transformers 4.8.2
- Pytorch 1.9.0+cu102
- Datasets 2.1.0
- Tokenizers 0.10.3
