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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: asl_aplhabet_img_classifier
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. -->
# asl_aplhabet_img_classifier
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: 2.9586
- Accuracy: 0.2692
## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 26 | 3.2666 | 0.0385 |
| No log | 2.0 | 52 | 3.2701 | 0.0385 |
| No log | 3.0 | 78 | 3.2713 | 0.0288 |
| No log | 4.0 | 104 | 3.2701 | 0.0769 |
| No log | 5.0 | 130 | 3.2584 | 0.0385 |
| No log | 6.0 | 156 | 3.2537 | 0.0577 |
| No log | 7.0 | 182 | 3.2402 | 0.0577 |
| No log | 8.0 | 208 | 3.2364 | 0.0577 |
| No log | 9.0 | 234 | 3.2055 | 0.0769 |
| No log | 10.0 | 260 | 3.1794 | 0.0769 |
| No log | 11.0 | 286 | 3.1851 | 0.1346 |
| No log | 12.0 | 312 | 3.1811 | 0.1058 |
| No log | 13.0 | 338 | 3.1594 | 0.1346 |
| No log | 14.0 | 364 | 3.1269 | 0.1635 |
| No log | 15.0 | 390 | 3.1082 | 0.125 |
| No log | 16.0 | 416 | 3.1019 | 0.2019 |
| No log | 17.0 | 442 | 3.0886 | 0.2019 |
| No log | 18.0 | 468 | 3.0599 | 0.2115 |
| No log | 19.0 | 494 | 3.0622 | 0.1731 |
| 3.0197 | 20.0 | 520 | 3.0474 | 0.1538 |
| 3.0197 | 21.0 | 546 | 3.0245 | 0.2115 |
| 3.0197 | 22.0 | 572 | 3.0386 | 0.1923 |
| 3.0197 | 23.0 | 598 | 3.0236 | 0.1923 |
| 3.0197 | 24.0 | 624 | 3.0201 | 0.1923 |
| 3.0197 | 25.0 | 650 | 3.0056 | 0.2212 |
| 3.0197 | 26.0 | 676 | 2.9649 | 0.25 |
| 3.0197 | 27.0 | 702 | 2.9900 | 0.2212 |
| 3.0197 | 28.0 | 728 | 2.9823 | 0.2308 |
| 3.0197 | 29.0 | 754 | 2.9782 | 0.2115 |
| 3.0197 | 30.0 | 780 | 3.0136 | 0.1635 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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