---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-yahd
  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-finetuned-yahd

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: 2.8670
- Accuracy: 0.1863

## 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.6746        | 1.0   | 919  | 2.5961          | 0.1324   |
| 2.3991        | 2.0   | 1838 | 2.5052          | 0.1448   |
| 2.036         | 3.0   | 2757 | 2.5028          | 0.1554   |
| 1.6838        | 4.0   | 3676 | 2.6002          | 0.1614   |
| 1.3583        | 5.0   | 4595 | 2.7135          | 0.1783   |
| 1.17          | 6.0   | 5514 | 2.8161          | 0.1787   |
| 1.0365        | 7.0   | 6433 | 2.8670          | 0.1863   |


### Framework versions

- Transformers 4.12.3
- Pytorch 1.9.0+cu102
- Datasets 1.15.1
- Tokenizers 0.10.3