---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased_fold_8_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_8_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: 1.6283
- F1: 0.8178

## 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  | 0.4038          | 0.7981 |
| 0.409         | 2.0   | 580  | 0.4023          | 0.8176 |
| 0.409         | 3.0   | 870  | 0.5245          | 0.8169 |
| 0.1938        | 4.0   | 1160 | 0.6242          | 0.8298 |
| 0.1938        | 5.0   | 1450 | 0.8432          | 0.8159 |
| 0.0848        | 6.0   | 1740 | 1.0887          | 0.8015 |
| 0.038         | 7.0   | 2030 | 1.0700          | 0.8167 |
| 0.038         | 8.0   | 2320 | 1.0970          | 0.8241 |
| 0.0159        | 9.0   | 2610 | 1.2474          | 0.8142 |
| 0.0159        | 10.0  | 2900 | 1.3453          | 0.8184 |
| 0.01          | 11.0  | 3190 | 1.4412          | 0.8147 |
| 0.01          | 12.0  | 3480 | 1.4263          | 0.8181 |
| 0.007         | 13.0  | 3770 | 1.3859          | 0.8258 |
| 0.0092        | 14.0  | 4060 | 1.4633          | 0.8128 |
| 0.0092        | 15.0  | 4350 | 1.4304          | 0.8206 |
| 0.0096        | 16.0  | 4640 | 1.5081          | 0.8149 |
| 0.0096        | 17.0  | 4930 | 1.5239          | 0.8189 |
| 0.0047        | 18.0  | 5220 | 1.5268          | 0.8151 |
| 0.0053        | 19.0  | 5510 | 1.5445          | 0.8173 |
| 0.0053        | 20.0  | 5800 | 1.6051          | 0.8180 |
| 0.0014        | 21.0  | 6090 | 1.5981          | 0.8211 |
| 0.0014        | 22.0  | 6380 | 1.5957          | 0.8225 |
| 0.001         | 23.0  | 6670 | 1.5838          | 0.8189 |
| 0.001         | 24.0  | 6960 | 1.6301          | 0.8178 |
| 0.0018        | 25.0  | 7250 | 1.6283          | 0.8178 |


### Framework versions

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