LABEL_0 LABEL_1 LABEL_2 LABEL_3
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-ft500_4class
  results: []
---

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# distilbert-base-uncased-finetuned-ft500_4class

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1343
- Accuracy: 0.4853
- F1: 0.4777

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.1837        | 1.0   | 188  | 1.1606          | 0.4313   | 0.4104 |
| 1.0972        | 2.0   | 376  | 1.0929          | 0.488    | 0.4697 |
| 1.0343        | 3.0   | 564  | 1.1017          | 0.4893   | 0.4651 |
| 0.9781        | 4.0   | 752  | 1.1065          | 0.4993   | 0.4900 |
| 0.9346        | 5.0   | 940  | 1.1343          | 0.4853   | 0.4777 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
