---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased_fold_6_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_6_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: 1.6838
- F1: 0.7881

## 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   | 290  | 0.4181          | 0.7732 |
| 0.4097        | 2.0   | 580  | 0.3967          | 0.7697 |
| 0.4097        | 3.0   | 870  | 0.5811          | 0.7797 |
| 0.2034        | 4.0   | 1160 | 0.8684          | 0.7320 |
| 0.2034        | 5.0   | 1450 | 0.9116          | 0.7718 |
| 0.0794        | 6.0   | 1740 | 1.0588          | 0.7690 |
| 0.0278        | 7.0   | 2030 | 1.2092          | 0.7738 |
| 0.0278        | 8.0   | 2320 | 1.2180          | 0.7685 |
| 0.0233        | 9.0   | 2610 | 1.3005          | 0.7676 |
| 0.0233        | 10.0  | 2900 | 1.4009          | 0.7634 |
| 0.0093        | 11.0  | 3190 | 1.4528          | 0.7805 |
| 0.0093        | 12.0  | 3480 | 1.4803          | 0.7859 |
| 0.0088        | 13.0  | 3770 | 1.4775          | 0.7750 |
| 0.0077        | 14.0  | 4060 | 1.6171          | 0.7699 |
| 0.0077        | 15.0  | 4350 | 1.6429          | 0.7636 |
| 0.0047        | 16.0  | 4640 | 1.5619          | 0.7819 |
| 0.0047        | 17.0  | 4930 | 1.5833          | 0.7724 |
| 0.0034        | 18.0  | 5220 | 1.6400          | 0.7853 |
| 0.0008        | 19.0  | 5510 | 1.6508          | 0.7792 |
| 0.0008        | 20.0  | 5800 | 1.6838          | 0.7881 |
| 0.0009        | 21.0  | 6090 | 1.6339          | 0.7829 |
| 0.0009        | 22.0  | 6380 | 1.6824          | 0.7806 |
| 0.0016        | 23.0  | 6670 | 1.6867          | 0.7876 |
| 0.0016        | 24.0  | 6960 | 1.7107          | 0.7877 |
| 0.0013        | 25.0  | 7250 | 1.6933          | 0.7812 |


### Framework versions

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