Downloads · 30 days
40
14% of all-time downloads
Birds-Species-classification
Hemg/Birds-Species-classification
Birds-Species-classification is a image classification model from Hemg. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
286
Public
Parameters
86.2M
44.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors345 MB · 100%
At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Mar 11, 2024
- Updated
- Mar 19, 2024
- SHA
- 435bfb25
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
Birds-Species-classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1943
- Accuracy: 0.9527
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: 0.0005
- 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: 16
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 5.2759 | 0.99 | 68 | 3.4103 | 0.86 |
| 1.7015 | 1.99 | 137 | 0.7510 | 0.8945 |
| 0.566 | 3.0 | 206 | 0.5793 | 0.8664 |
| 0.4301 | 4.0 | 275 | 0.4694 | 0.8909 |
| 0.3603 | 4.99 | 343 | 0.3995 | 0.9036 |
| 0.3032 | 5.99 | 412 | 0.3757 | 0.9036 |
| 0.2632 | 7.0 | 481 | 0.3843 | 0.9059 |
| 0.2211 | 8.0 | 550 | 0.3490 | 0.9123 |
| 0.1929 | 8.99 | 618 | 0.3618 | 0.9045 |
| 0.1645 | 9.99 | 687 | 0.2970 | 0.9241 |
| 0.1621 | 11.0 | 756 | 0.2874 | 0.93 |
| 0.1337 | 12.0 | 825 | 0.2705 | 0.9391 |
| 0.1238 | 12.99 | 893 | 0.2231 | 0.9436 |
| 0.1096 | 13.99 | 962 | 0.2440 | 0.9441 |
| 0.0979 | 15.0 | 1031 | 0.2371 | 0.9423 |
| 0.0808 | 15.83 | 1088 | 0.1943 | 0.9527 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Mar 11, 2024
- Updated
- Mar 19, 2024