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# 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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "sign_language_classification_v1", "results": []}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer base_model:google/vit-base-patch16-224-in21k license:apache-2.0 autotrain_compatible endpoints_compatible region:us