update model card README.md
Browse files
README.md
ADDED
@@ -0,0 +1,85 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
tags:
|
4 |
+
- generated_from_trainer
|
5 |
+
datasets:
|
6 |
+
- imagefolder
|
7 |
+
metrics:
|
8 |
+
- accuracy
|
9 |
+
model-index:
|
10 |
+
- name: regnet-y-064-Brain_Tumors_Image_Classification
|
11 |
+
results:
|
12 |
+
- task:
|
13 |
+
name: Image Classification
|
14 |
+
type: image-classification
|
15 |
+
dataset:
|
16 |
+
name: imagefolder
|
17 |
+
type: imagefolder
|
18 |
+
config: default
|
19 |
+
split: train
|
20 |
+
args: default
|
21 |
+
metrics:
|
22 |
+
- name: Accuracy
|
23 |
+
type: accuracy
|
24 |
+
value: 0.8045685279187818
|
25 |
+
---
|
26 |
+
|
27 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
28 |
+
should probably proofread and complete it, then remove this comment. -->
|
29 |
+
|
30 |
+
# regnet-y-064-Brain_Tumors_Image_Classification
|
31 |
+
|
32 |
+
This model is a fine-tuned version of [facebook/regnet-y-064](https://huggingface.co/facebook/regnet-y-064) on the imagefolder dataset.
|
33 |
+
It achieves the following results on the evaluation set:
|
34 |
+
- Loss: 1.1561
|
35 |
+
- Accuracy: 0.8046
|
36 |
+
- Weighted f1: 0.7776
|
37 |
+
- Micro f1: 0.8046
|
38 |
+
- Macro f1: 0.7839
|
39 |
+
- Weighted recall: 0.8046
|
40 |
+
- Micro recall: 0.8046
|
41 |
+
- Macro recall: 0.7978
|
42 |
+
- Weighted precision: 0.8574
|
43 |
+
- Micro precision: 0.8046
|
44 |
+
- Macro precision: 0.8736
|
45 |
+
|
46 |
+
## Model description
|
47 |
+
|
48 |
+
More information needed
|
49 |
+
|
50 |
+
## Intended uses & limitations
|
51 |
+
|
52 |
+
More information needed
|
53 |
+
|
54 |
+
## Training and evaluation data
|
55 |
+
|
56 |
+
More information needed
|
57 |
+
|
58 |
+
## Training procedure
|
59 |
+
|
60 |
+
### Training hyperparameters
|
61 |
+
|
62 |
+
The following hyperparameters were used during training:
|
63 |
+
- learning_rate: 0.0002
|
64 |
+
- train_batch_size: 16
|
65 |
+
- eval_batch_size: 8
|
66 |
+
- seed: 42
|
67 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
68 |
+
- lr_scheduler_type: linear
|
69 |
+
- num_epochs: 3
|
70 |
+
|
71 |
+
### Training results
|
72 |
+
|
73 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
|
74 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
|
75 |
+
| 1.288 | 1.0 | 180 | 1.3796 | 0.6548 | 0.5991 | 0.6548 | 0.5868 | 0.6548 | 0.6548 | 0.6176 | 0.8046 | 0.6548 | 0.8285 |
|
76 |
+
| 1.288 | 2.0 | 360 | 1.0964 | 0.7944 | 0.7687 | 0.7944 | 0.7755 | 0.7944 | 0.7944 | 0.7872 | 0.8555 | 0.7944 | 0.8727 |
|
77 |
+
| 0.1498 | 3.0 | 540 | 1.1561 | 0.8046 | 0.7776 | 0.8046 | 0.7839 | 0.8046 | 0.8046 | 0.7978 | 0.8574 | 0.8046 | 0.8736 |
|
78 |
+
|
79 |
+
|
80 |
+
### Framework versions
|
81 |
+
|
82 |
+
- Transformers 4.28.1
|
83 |
+
- Pytorch 2.0.0
|
84 |
+
- Datasets 2.11.0
|
85 |
+
- Tokenizers 0.13.3
|