---
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-2024-02-10
  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: 0.747
    - name: F1
      type: f1
      value: 0.6949375855120276
---

<!-- 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-2024-02-10

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: 0.7689
- Accuracy: 0.747
- F1: 0.6949

## 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: 1e-06
- 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: 9

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.331         | 1.0   | 250  | 1.2185          | 0.572    | 0.4495 |
| 1.1818        | 2.0   | 500  | 1.1132          | 0.5905   | 0.4665 |
| 1.0888        | 3.0   | 750  | 1.0287          | 0.6235   | 0.5262 |
| 1.0059        | 4.0   | 1000 | 0.9443          | 0.6905   | 0.6258 |
| 0.9335        | 5.0   | 1250 | 0.8771          | 0.7135   | 0.6539 |
| 0.872         | 6.0   | 1500 | 0.8277          | 0.7285   | 0.6726 |
| 0.8313        | 7.0   | 1750 | 0.7945          | 0.741    | 0.6871 |
| 0.8047        | 8.0   | 2000 | 0.7757          | 0.747    | 0.6942 |
| 0.7931        | 9.0   | 2250 | 0.7689          | 0.747    | 0.6949 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1