---
base_model: distilbert/distilbert-base-uncased
library_name: peft
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: dbert-peft-rating
  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. -->

# dbert-peft-rating

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0726
- Accuracy: 0.4988
- Mse: 0.8475

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Mse    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 425  | 1.2773          | 0.4119   | 1.1295 |
| 1.3444        | 2.0   | 850  | 1.1427          | 0.4706   | 0.8780 |
| 1.1864        | 3.0   | 1275 | 1.1049          | 0.4885   | 0.8633 |
| 1.1177        | 4.0   | 1700 | 1.0943          | 0.4892   | 0.8169 |
| 1.0957        | 5.0   | 2125 | 1.0881          | 0.4923   | 0.8172 |
| 1.0893        | 6.0   | 2550 | 1.0814          | 0.4933   | 0.8636 |
| 1.0893        | 7.0   | 2975 | 1.0781          | 0.4943   | 0.8324 |
| 1.0761        | 8.0   | 3400 | 1.0749          | 0.4991   | 0.8464 |
| 1.0687        | 9.0   | 3825 | 1.0727          | 0.5002   | 0.8530 |
| 1.0668        | 10.0  | 4250 | 1.0726          | 0.4988   | 0.8475 |


### Framework versions

- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1