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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: quality_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. -->

# quality_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: 0.0104
- Mse: 0.0104

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0154        | 0.05  | 50   | 0.0106          | 0.0106 |
| 0.0172        | 0.11  | 100  | 0.0109          | 0.0109 |
| 0.0166        | 0.16  | 150  | 0.0199          | 0.0199 |
| 0.0132        | 0.22  | 200  | 0.0106          | 0.0106 |
| 0.0153        | 0.27  | 250  | 0.0120          | 0.0120 |
| 0.0131        | 0.32  | 300  | 0.0104          | 0.0104 |
| 0.0127        | 0.38  | 350  | 0.0104          | 0.0104 |
| 0.0143        | 0.43  | 400  | 0.0110          | 0.0110 |
| 0.0146        | 0.48  | 450  | 0.0113          | 0.0113 |
| 0.0119        | 0.54  | 500  | 0.0115          | 0.0115 |
| 0.0172        | 0.59  | 550  | 0.0107          | 0.0107 |
| 0.0111        | 0.65  | 600  | 0.0104          | 0.0104 |
| 0.0114        | 0.7   | 650  | 0.0105          | 0.0105 |
| 0.0219        | 0.75  | 700  | 0.0106          | 0.0106 |
| 0.0118        | 0.81  | 750  | 0.0122          | 0.0122 |
| 0.0184        | 0.86  | 800  | 0.0104          | 0.0104 |
| 0.0176        | 0.92  | 850  | 0.0104          | 0.0104 |
| 0.0137        | 0.97  | 900  | 0.0104          | 0.0104 |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2