---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SS_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# SS_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: 0.3980
- Accuracy: 0.9587

## 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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.153         | 1.0   | 4301  | 0.1472          | 0.9526   |
| 0.1165        | 2.0   | 8602  | 0.1376          | 0.9562   |
| 0.0951        | 3.0   | 12903 | 0.1462          | 0.9596   |
| 0.0851        | 4.0   | 17204 | 0.1550          | 0.9602   |
| 0.0709        | 5.0   | 21505 | 0.1848          | 0.9596   |
| 0.069         | 6.0   | 25806 | 0.2027          | 0.9586   |
| 0.0591        | 7.0   | 30107 | 0.2266          | 0.9582   |
| 0.047         | 8.0   | 34408 | 0.2110          | 0.9573   |
| 0.0391        | 9.0   | 38709 | 0.2405          | 0.9577   |
| 0.0333        | 10.0  | 43010 | 0.2865          | 0.9566   |
| 0.0336        | 11.0  | 47311 | 0.2671          | 0.9588   |
| 0.0226        | 12.0  | 51612 | 0.2743          | 0.9567   |
| 0.0266        | 13.0  | 55913 | 0.3281          | 0.9577   |
| 0.0191        | 14.0  | 60214 | 0.3062          | 0.9572   |
| 0.0232        | 15.0  | 64515 | 0.3479          | 0.9585   |
| 0.0149        | 16.0  | 68816 | 0.3542          | 0.9587   |
| 0.0099        | 17.0  | 73117 | 0.3646          | 0.9587   |
| 0.0123        | 18.0  | 77418 | 0.3721          | 0.9584   |
| 0.0091        | 19.0  | 81719 | 0.3896          | 0.9590   |
| 0.0086        | 20.0  | 86020 | 0.3980          | 0.9587   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3