Model save
Browse files
README.md
ADDED
|
@@ -0,0 +1,89 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
base_model: facebook/convnextv2-tiny-22k-384
|
| 4 |
+
tags:
|
| 5 |
+
- generated_from_trainer
|
| 6 |
+
datasets:
|
| 7 |
+
- imagefolder
|
| 8 |
+
metrics:
|
| 9 |
+
- accuracy
|
| 10 |
+
model-index:
|
| 11 |
+
- name: cconvnext-tiny-15ep-1e-4
|
| 12 |
+
results:
|
| 13 |
+
- task:
|
| 14 |
+
name: Image Classification
|
| 15 |
+
type: image-classification
|
| 16 |
+
dataset:
|
| 17 |
+
name: imagefolder
|
| 18 |
+
type: imagefolder
|
| 19 |
+
config: default
|
| 20 |
+
split: validation
|
| 21 |
+
args: default
|
| 22 |
+
metrics:
|
| 23 |
+
- name: Accuracy
|
| 24 |
+
type: accuracy
|
| 25 |
+
value: 0.9355864811133201
|
| 26 |
+
---
|
| 27 |
+
|
| 28 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 29 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 30 |
+
|
| 31 |
+
# cconvnext-tiny-15ep-1e-4
|
| 32 |
+
|
| 33 |
+
This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on the imagefolder dataset.
|
| 34 |
+
It achieves the following results on the evaluation set:
|
| 35 |
+
- Loss: 0.2902
|
| 36 |
+
- Accuracy: 0.9356
|
| 37 |
+
|
| 38 |
+
## Model description
|
| 39 |
+
|
| 40 |
+
More information needed
|
| 41 |
+
|
| 42 |
+
## Intended uses & limitations
|
| 43 |
+
|
| 44 |
+
More information needed
|
| 45 |
+
|
| 46 |
+
## Training and evaluation data
|
| 47 |
+
|
| 48 |
+
More information needed
|
| 49 |
+
|
| 50 |
+
## Training procedure
|
| 51 |
+
|
| 52 |
+
### Training hyperparameters
|
| 53 |
+
|
| 54 |
+
The following hyperparameters were used during training:
|
| 55 |
+
- learning_rate: 0.0001
|
| 56 |
+
- train_batch_size: 32
|
| 57 |
+
- eval_batch_size: 32
|
| 58 |
+
- seed: 42
|
| 59 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 60 |
+
- lr_scheduler_type: cosine
|
| 61 |
+
- num_epochs: 15
|
| 62 |
+
|
| 63 |
+
### Training results
|
| 64 |
+
|
| 65 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 66 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| 67 |
+
| 0.5838 | 1.0 | 550 | 0.4097 | 0.8811 |
|
| 68 |
+
| 0.4565 | 2.0 | 1100 | 0.4269 | 0.8763 |
|
| 69 |
+
| 0.3628 | 3.0 | 1650 | 0.3464 | 0.9002 |
|
| 70 |
+
| 0.2915 | 4.0 | 2200 | 0.3366 | 0.9066 |
|
| 71 |
+
| 0.2655 | 5.0 | 2750 | 0.3387 | 0.9054 |
|
| 72 |
+
| 0.2395 | 6.0 | 3300 | 0.3313 | 0.9125 |
|
| 73 |
+
| 0.2065 | 7.0 | 3850 | 0.3120 | 0.9181 |
|
| 74 |
+
| 0.1503 | 8.0 | 4400 | 0.3065 | 0.9221 |
|
| 75 |
+
| 0.1503 | 9.0 | 4950 | 0.2948 | 0.9276 |
|
| 76 |
+
| 0.1125 | 10.0 | 5500 | 0.2918 | 0.9304 |
|
| 77 |
+
| 0.1057 | 11.0 | 6050 | 0.2954 | 0.9328 |
|
| 78 |
+
| 0.0937 | 12.0 | 6600 | 0.2959 | 0.9336 |
|
| 79 |
+
| 0.0966 | 13.0 | 7150 | 0.2940 | 0.9352 |
|
| 80 |
+
| 0.0735 | 14.0 | 7700 | 0.2916 | 0.9340 |
|
| 81 |
+
| 0.0881 | 15.0 | 8250 | 0.2902 | 0.9356 |
|
| 82 |
+
|
| 83 |
+
|
| 84 |
+
### Framework versions
|
| 85 |
+
|
| 86 |
+
- Transformers 4.39.3
|
| 87 |
+
- Pytorch 2.1.2
|
| 88 |
+
- Datasets 2.18.0
|
| 89 |
+
- Tokenizers 0.15.2
|