File size: 2,547 Bytes
176b690 |
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 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 |
---
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- f1
model-index:
- name: dinov2-base-finetuned-Leukemia
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 1.0
- name: F1
type: f1
value: 1.0
---
<!-- 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. -->
# dinov2-base-finetuned-Leukemia
This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0
- F1: 1.0
## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.0541 | 0.9954 | 162 | 0.8475 | 0.9018 | 0.9047 |
| 0.0667 | 1.9969 | 325 | 0.0745 | 0.9785 | 0.9780 |
| 0.1317 | 2.9985 | 488 | 0.0159 | 0.9939 | 0.9939 |
| 0.0187 | 4.0 | 651 | 0.0771 | 0.9877 | 0.9878 |
| 0.0762 | 4.9954 | 813 | 0.1135 | 0.9877 | 0.9878 |
| 0.006 | 5.9969 | 976 | 0.0502 | 0.9969 | 0.9969 |
| 0.1322 | 6.9985 | 1139 | 0.0357 | 0.9969 | 0.9969 |
| 0.0332 | 8.0 | 1302 | 0.0000 | 1.0 | 1.0 |
| 0.0 | 8.9954 | 1464 | 0.0004 | 1.0 | 1.0 |
| 0.0 | 9.9539 | 1620 | 0.0000 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
|