---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased_fold_1_binary
  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_fold_1_binary

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: 1.1222
- F1: 0.7596

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 288  | 0.4130          | 0.7517 |
| 0.3938        | 2.0   | 576  | 0.4260          | 0.7330 |
| 0.3938        | 3.0   | 864  | 0.5000          | 0.7488 |
| 0.19          | 4.0   | 1152 | 0.7415          | 0.7487 |
| 0.19          | 5.0   | 1440 | 0.8994          | 0.7397 |
| 0.0903        | 6.0   | 1728 | 0.9835          | 0.7386 |
| 0.0392        | 7.0   | 2016 | 1.1222          | 0.7596 |
| 0.0392        | 8.0   | 2304 | 1.2018          | 0.7314 |
| 0.0234        | 9.0   | 2592 | 1.2691          | 0.7330 |
| 0.0234        | 10.0  | 2880 | 1.2972          | 0.7496 |
| 0.0182        | 11.0  | 3168 | 1.4606          | 0.7492 |
| 0.0182        | 12.0  | 3456 | 1.4766          | 0.7361 |
| 0.006         | 13.0  | 3744 | 1.4888          | 0.7500 |
| 0.0057        | 14.0  | 4032 | 1.5684          | 0.7298 |
| 0.0057        | 15.0  | 4320 | 1.5354          | 0.7509 |
| 0.0058        | 16.0  | 4608 | 1.7733          | 0.7436 |
| 0.0058        | 17.0  | 4896 | 1.5695          | 0.7512 |
| 0.0089        | 18.0  | 5184 | 1.6593          | 0.7430 |
| 0.0089        | 19.0  | 5472 | 1.7092          | 0.7444 |
| 0.0048        | 20.0  | 5760 | 1.7206          | 0.7374 |
| 0.002         | 21.0  | 6048 | 1.7440          | 0.7343 |
| 0.002         | 22.0  | 6336 | 1.7582          | 0.7347 |
| 0.0006        | 23.0  | 6624 | 1.7294          | 0.7472 |
| 0.0006        | 24.0  | 6912 | 1.7454          | 0.7365 |
| 0.0001        | 25.0  | 7200 | 1.7395          | 0.7429 |


### Framework versions

- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1