File size: 1,782 Bytes
41c5279 74c90db 41c5279 74c90db 41c5279 74c90db 41c5279 74c90db 41c5279 74c90db 41c5279 74c90db 41c5279 74c90db 41c5279 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-diabetic-retinopathy-classification
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. -->
# vit-diabetic-retinopathy-classification
This model is a fine-tuned version of [Kontawat/vit-diabetic-retinopathy-classification](https://huggingface.co/Kontawat/vit-diabetic-retinopathy-classification) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0460
- Accuracy: 0.7287
## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5645 | 0.94 | 100 | 0.7731 | 0.7239 |
| 0.3971 | 1.89 | 200 | 0.8123 | 0.7038 |
| 0.3239 | 2.83 | 300 | 0.8204 | 0.7239 |
| 0.2178 | 3.77 | 400 | 0.9085 | 0.7204 |
| 0.18 | 4.72 | 500 | 1.0284 | 0.7310 |
| 0.0501 | 5.66 | 600 | 1.0460 | 0.7287 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2
|