|
--- |
|
license: apache-2.0 |
|
base_model: google/vit-base-patch16-224-in21k |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: sign_language_classification_v1 |
|
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. --> |
|
|
|
# sign_language_classification_v1 |
|
|
|
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.3445 |
|
- Accuracy: 0.8056 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 64 |
|
- eval_batch_size: 64 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 50 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 3.2889 | 1.0 | 8 | 3.2714 | 0.0556 | |
|
| 3.2492 | 2.0 | 16 | 3.2615 | 0.125 | |
|
| 3.2263 | 3.0 | 24 | 3.2034 | 0.125 | |
|
| 3.1271 | 4.0 | 32 | 3.1297 | 0.2083 | |
|
| 2.9592 | 5.0 | 40 | 3.0655 | 0.2639 | |
|
| 2.9414 | 6.0 | 48 | 2.9282 | 0.3472 | |
|
| 2.7337 | 7.0 | 56 | 2.8254 | 0.4028 | |
|
| 2.6683 | 8.0 | 64 | 2.6909 | 0.4583 | |
|
| 2.5837 | 9.0 | 72 | 2.5904 | 0.5417 | |
|
| 2.4566 | 10.0 | 80 | 2.5380 | 0.5833 | |
|
| 2.2188 | 11.0 | 88 | 2.4682 | 0.5417 | |
|
| 2.2885 | 12.0 | 96 | 2.3196 | 0.5833 | |
|
| 2.005 | 13.0 | 104 | 2.2824 | 0.6667 | |
|
| 1.9293 | 14.0 | 112 | 2.1967 | 0.6389 | |
|
| 1.8396 | 15.0 | 120 | 2.0287 | 0.7361 | |
|
| 1.7066 | 16.0 | 128 | 2.0357 | 0.7361 | |
|
| 1.6911 | 17.0 | 136 | 1.9670 | 0.7361 | |
|
| 1.6285 | 18.0 | 144 | 1.9186 | 0.7361 | |
|
| 1.6064 | 19.0 | 152 | 1.9239 | 0.6944 | |
|
| 1.6067 | 20.0 | 160 | 1.7723 | 0.7778 | |
|
| 1.4094 | 21.0 | 168 | 1.7701 | 0.75 | |
|
| 1.4664 | 22.0 | 176 | 1.7453 | 0.75 | |
|
| 1.3255 | 23.0 | 184 | 1.7103 | 0.7083 | |
|
| 1.3253 | 24.0 | 192 | 1.7216 | 0.7778 | |
|
| 1.2416 | 25.0 | 200 | 1.5770 | 0.7778 | |
|
| 1.1696 | 26.0 | 208 | 1.5099 | 0.7917 | |
|
| 1.1645 | 27.0 | 216 | 1.4630 | 0.7917 | |
|
| 1.0646 | 28.0 | 224 | 1.4989 | 0.7917 | |
|
| 1.0149 | 29.0 | 232 | 1.5569 | 0.7222 | |
|
| 1.0799 | 30.0 | 240 | 1.3602 | 0.8333 | |
|
| 0.9528 | 31.0 | 248 | 1.3782 | 0.8472 | |
|
| 1.0461 | 32.0 | 256 | 1.3698 | 0.8333 | |
|
| 0.9019 | 33.0 | 264 | 1.3251 | 0.8611 | |
|
| 0.9494 | 34.0 | 272 | 1.3586 | 0.8472 | |
|
| 0.9439 | 35.0 | 280 | 1.3526 | 0.8333 | |
|
| 0.9089 | 36.0 | 288 | 1.2728 | 0.8333 | |
|
| 0.8962 | 37.0 | 296 | 1.3006 | 0.7917 | |
|
| 0.9482 | 38.0 | 304 | 1.2592 | 0.8611 | |
|
| 0.8804 | 39.0 | 312 | 1.3527 | 0.7778 | |
|
| 0.8348 | 40.0 | 320 | 1.2759 | 0.8056 | |
|
| 0.7823 | 41.0 | 328 | 1.3071 | 0.8194 | |
|
| 0.8944 | 42.0 | 336 | 1.2428 | 0.8194 | |
|
| 0.9677 | 43.0 | 344 | 1.2903 | 0.7778 | |
|
| 0.9584 | 44.0 | 352 | 1.3119 | 0.7639 | |
|
| 0.8342 | 45.0 | 360 | 1.3502 | 0.7778 | |
|
| 0.7878 | 46.0 | 368 | 1.1941 | 0.8333 | |
|
| 0.7817 | 47.0 | 376 | 1.2670 | 0.8056 | |
|
| 0.812 | 48.0 | 384 | 1.2068 | 0.8194 | |
|
| 0.9714 | 49.0 | 392 | 1.3480 | 0.75 | |
|
| 0.9362 | 50.0 | 400 | 1.4028 | 0.7083 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|