---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_awesome_model
  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. -->

# my_awesome_model

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: 0.7495
- Accuracy: 0.8383

## 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: 1e-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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 84   | 0.4945          | 0.8024   |
| No log        | 2.0   | 168  | 0.4300          | 0.8383   |
| No log        | 3.0   | 252  | 0.4170          | 0.8144   |
| No log        | 4.0   | 336  | 0.4209          | 0.8503   |
| No log        | 5.0   | 420  | 0.5133          | 0.8204   |
| 0.3035        | 6.0   | 504  | 0.6426          | 0.7994   |
| 0.3035        | 7.0   | 588  | 0.5828          | 0.8353   |
| 0.3035        | 8.0   | 672  | 0.6595          | 0.8234   |
| 0.3035        | 9.0   | 756  | 0.7512          | 0.8383   |
| 0.3035        | 10.0  | 840  | 0.7080          | 0.8263   |
| 0.3035        | 11.0  | 924  | 0.7231          | 0.8473   |
| 0.0326        | 12.0  | 1008 | 0.7571          | 0.8383   |
| 0.0326        | 13.0  | 1092 | 0.7440          | 0.8383   |
| 0.0326        | 14.0  | 1176 | 0.7603          | 0.8413   |
| 0.0326        | 15.0  | 1260 | 0.7495          | 0.8383   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3