---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased_fold_3_binary_v1
  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_3_binary_v1

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: 1.9405
- F1: 0.7878

## 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   | 289  | 0.4630          | 0.7897 |
| 0.3954        | 2.0   | 578  | 0.4549          | 0.7936 |
| 0.3954        | 3.0   | 867  | 0.6527          | 0.7868 |
| 0.1991        | 4.0   | 1156 | 0.7510          | 0.7951 |
| 0.1991        | 5.0   | 1445 | 0.9327          | 0.8000 |
| 0.095         | 6.0   | 1734 | 1.0974          | 0.7859 |
| 0.0347        | 7.0   | 2023 | 1.2692          | 0.7919 |
| 0.0347        | 8.0   | 2312 | 1.3718          | 0.7921 |
| 0.0105        | 9.0   | 2601 | 1.4679          | 0.7999 |
| 0.0105        | 10.0  | 2890 | 1.5033          | 0.8070 |
| 0.0079        | 11.0  | 3179 | 1.6074          | 0.8008 |
| 0.0079        | 12.0  | 3468 | 1.6921          | 0.7904 |
| 0.0053        | 13.0  | 3757 | 1.7079          | 0.7945 |
| 0.0054        | 14.0  | 4046 | 1.8361          | 0.7887 |
| 0.0054        | 15.0  | 4335 | 1.7695          | 0.7873 |
| 0.0046        | 16.0  | 4624 | 1.7934          | 0.7917 |
| 0.0046        | 17.0  | 4913 | 1.8036          | 0.8008 |
| 0.0064        | 18.0  | 5202 | 1.8780          | 0.7888 |
| 0.0064        | 19.0  | 5491 | 1.8943          | 0.7923 |
| 0.0032        | 20.0  | 5780 | 1.8694          | 0.7905 |
| 0.002         | 21.0  | 6069 | 1.9348          | 0.7869 |
| 0.002         | 22.0  | 6358 | 1.9578          | 0.7804 |
| 0.0036        | 23.0  | 6647 | 1.9438          | 0.7827 |
| 0.0036        | 24.0  | 6936 | 1.9386          | 0.7878 |
| 0.0011        | 25.0  | 7225 | 1.9405          | 0.7878 |


### Framework versions

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