---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
- precision
model-index:
- name: distilbert-base-uncased_emotion_ft_0416
  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: 0.9376066970307232
    - name: Precision
      type: precision
      value: 0.907678056501393
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased_emotion_ft_0416

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: 0.1420
- Accuracy: 0.9375
- F1: 0.9376
- Precision: 0.9077

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
| 0.2093        | 1.0   | 250  | 0.1715          | 0.9345   | 0.9349 | 0.9042    |
| 0.1325        | 2.0   | 500  | 0.1523          | 0.9335   | 0.9340 | 0.8994    |
| 0.1017        | 3.0   | 750  | 0.1437          | 0.9365   | 0.9369 | 0.9029    |
| 0.08          | 4.0   | 1000 | 0.1420          | 0.9375   | 0.9376 | 0.9077    |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1