---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
model-index:
- name: distilbert-base-uncased_Devign_ft_0920
  results: []
---

<!-- 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_Devign_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: 0.6628
- Accuracy: 0.6207
- F1: 0.6212
- Precision: 0.6181

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
| 0.6722        | 1.0   | 683  | 0.6534          | 0.5936   | 0.5299 | 0.6232    |
| 0.612         | 2.0   | 1366 | 0.6247          | 0.6258   | 0.6238 | 0.6209    |
| 0.5647        | 3.0   | 2049 | 0.6289          | 0.6250   | 0.6256 | 0.6224    |
| 0.5176        | 4.0   | 2732 | 0.6628          | 0.6207   | 0.6212 | 0.6181    |


### Framework versions

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