---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_awesome_model_3
  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_3

This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0954
- Accuracy: 0.9680

## 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.09  | 200  | 0.2369          | 0.9040   |
| No log        | 0.19  | 400  | 0.1859          | 0.9324   |
| 0.2931        | 0.28  | 600  | 0.1624          | 0.9442   |
| 0.2931        | 0.38  | 800  | 0.1194          | 0.9569   |
| 0.1456        | 0.47  | 1000 | 0.1245          | 0.9588   |
| 0.1456        | 0.57  | 1200 | 0.1044          | 0.9617   |
| 0.1456        | 0.66  | 1400 | 0.1063          | 0.9611   |
| 0.1194        | 0.75  | 1600 | 0.1021          | 0.9634   |
| 0.1194        | 0.85  | 1800 | 0.1618          | 0.9490   |
| 0.1107        | 0.94  | 2000 | 0.1113          | 0.9643   |
| 0.1107        | 1.04  | 2200 | 0.1163          | 0.9630   |
| 0.1107        | 1.13  | 2400 | 0.0954          | 0.9680   |
| 0.079         | 1.22  | 2600 | 0.1272          | 0.9635   |
| 0.079         | 1.32  | 2800 | 0.0976          | 0.9657   |
| 0.0715        | 1.41  | 3000 | 0.0995          | 0.9680   |
| 0.0715        | 1.51  | 3200 | 0.0996          | 0.9660   |
| 0.0715        | 1.6   | 3400 | 0.1001          | 0.9670   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2