---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
- precision
model-index:
- name: distilbert-base-uncased_emotion_ft_0526
  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: 0.9375
    - name: F1
      type: f1
      value: 0.937552703246777
    - name: Precision
      type: precision
      value: 0.9169515578018389
---

<!-- 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_emotion_ft_0526

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: 0.2275
- Accuracy: 0.9375
- F1: 0.9376
- Precision: 0.9170

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
| 0.2131        | 1.0   | 2000 | 0.2301          | 0.93     | 0.9305 | 0.9008    |
| 0.1881        | 2.0   | 4000 | 0.1854          | 0.9385   | 0.9388 | 0.9080    |
| 0.1012        | 3.0   | 6000 | 0.2200          | 0.935    | 0.9353 | 0.9066    |
| 0.0642        | 4.0   | 8000 | 0.2275          | 0.9375   | 0.9376 | 0.9170    |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3