
<!-- 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. -->

# cvt-13-finetuned-IDRiD

This model is a fine-tuned version of [microsoft/cvt-13](https://huggingface.co/microsoft/cvt-13) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2520
- Accuracy: 0.4524

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 3    | 1.6800          | 0.1190   |
| No log        | 2.0   | 6    | 1.6686          | 0.2143   |
| No log        | 3.0   | 9    | 1.5528          | 0.3333   |
| 1.6061        | 4.0   | 12   | 1.4874          | 0.3333   |
| 1.6061        | 5.0   | 15   | 1.4834          | 0.3571   |
| 1.6061        | 6.0   | 18   | 1.4485          | 0.3810   |
| 1.4325        | 7.0   | 21   | 1.4295          | 0.4048   |
| 1.4325        | 8.0   | 24   | 1.4172          | 0.4286   |
| 1.4325        | 9.0   | 27   | 1.3890          | 0.4048   |
| 1.3474        | 10.0  | 30   | 1.3739          | 0.4286   |
| 1.3474        | 11.0  | 33   | 1.3571          | 0.4048   |
| 1.3474        | 12.0  | 36   | 1.3244          | 0.4048   |
| 1.3474        | 13.0  | 39   | 1.3090          | 0.4048   |
| 1.3039        | 14.0  | 42   | 1.3438          | 0.4286   |
| 1.3039        | 15.0  | 45   | 1.3617          | 0.4286   |
| 1.3039        | 16.0  | 48   | 1.3513          | 0.4286   |
| 1.2892        | 17.0  | 51   | 1.3187          | 0.4524   |
| 1.2892        | 18.0  | 54   | 1.3054          | 0.3810   |
| 1.2892        | 19.0  | 57   | 1.2862          | 0.4286   |
| 1.2489        | 20.0  | 60   | 1.2670          | 0.4524   |
| 1.2489        | 21.0  | 63   | 1.2810          | 0.4762   |
| 1.2489        | 22.0  | 66   | 1.2389          | 0.4524   |
| 1.2489        | 23.0  | 69   | 1.2312          | 0.4762   |
| 1.2378        | 24.0  | 72   | 1.2619          | 0.4524   |
| 1.2378        | 25.0  | 75   | 1.2652          | 0.4524   |
| 1.2378        | 26.0  | 78   | 1.2639          | 0.4524   |
| 1.1968        | 27.0  | 81   | 1.2517          | 0.4524   |
| 1.1968        | 28.0  | 84   | 1.2603          | 0.4286   |
| 1.1968        | 29.0  | 87   | 1.2463          | 0.4524   |
| 1.1977        | 30.0  | 90   | 1.2520          | 0.4524   |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.13.3

a_nodr b_milddr c_moderatedr d_severedr e_prodr