---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
model-index:
- name: distilbert-base-uncased_reveal_ft_0920
  results: []
---

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# distilbert-base-uncased_reveal_ft_0920

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2843
- Accuracy: 0.8937
- F1: 0.8779
- Precision: 0.6909

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
| 0.2967        | 1.0   | 341  | 0.3203          | 0.8975   | 0.8490 | 0.4487    |
| 0.2715        | 2.0   | 682  | 0.2838          | 0.8975   | 0.8492 | 0.6988    |
| 0.2388        | 3.0   | 1023 | 0.2808          | 0.9002   | 0.8733 | 0.7302    |
| 0.2157        | 4.0   | 1364 | 0.2843          | 0.8937   | 0.8779 | 0.6909    |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.2.2
- Datasets 2.16.1
- Tokenizers 0.13.3