---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased_fold_9_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_9_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: 1.6965
- F1: 0.8090

## 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   | 291  | 0.4193          | 0.7989 |
| 0.3993        | 2.0   | 582  | 0.4039          | 0.8026 |
| 0.3993        | 3.0   | 873  | 0.5227          | 0.7995 |
| 0.2044        | 4.0   | 1164 | 0.7264          | 0.8011 |
| 0.2044        | 5.0   | 1455 | 0.8497          | 0.8007 |
| 0.0882        | 6.0   | 1746 | 0.9543          | 0.8055 |
| 0.0374        | 7.0   | 2037 | 1.1349          | 0.7997 |
| 0.0374        | 8.0   | 2328 | 1.3175          | 0.8009 |
| 0.0151        | 9.0   | 2619 | 1.3585          | 0.8030 |
| 0.0151        | 10.0  | 2910 | 1.4202          | 0.8067 |
| 0.0068        | 11.0  | 3201 | 1.4364          | 0.8108 |
| 0.0068        | 12.0  | 3492 | 1.4443          | 0.8088 |
| 0.0096        | 13.0  | 3783 | 1.5308          | 0.8075 |
| 0.0031        | 14.0  | 4074 | 1.5061          | 0.8020 |
| 0.0031        | 15.0  | 4365 | 1.5769          | 0.7980 |
| 0.0048        | 16.0  | 4656 | 1.5962          | 0.8038 |
| 0.0048        | 17.0  | 4947 | 1.5383          | 0.8085 |
| 0.0067        | 18.0  | 5238 | 1.5456          | 0.8158 |
| 0.0062        | 19.0  | 5529 | 1.6325          | 0.8044 |
| 0.0062        | 20.0  | 5820 | 1.5430          | 0.8141 |
| 0.0029        | 21.0  | 6111 | 1.6590          | 0.8117 |
| 0.0029        | 22.0  | 6402 | 1.6650          | 0.8112 |
| 0.0017        | 23.0  | 6693 | 1.7016          | 0.8053 |
| 0.0017        | 24.0  | 6984 | 1.6998          | 0.8090 |
| 0.0011        | 25.0  | 7275 | 1.6965          | 0.8090 |


### Framework versions

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