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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_v3
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_v3
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: 1.7922
- Accuracy: 0.7549
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 272 | 3.0038 | 0.3802 |
| 3.0097 | 2.0 | 544 | 2.5739 | 0.5880 |
| 3.0097 | 3.0 | 816 | 2.2886 | 0.6464 |
| 2.3653 | 4.0 | 1088 | 2.0810 | 0.7099 |
| 2.3653 | 5.0 | 1360 | 1.9355 | 0.7407 |
| 1.9884 | 6.0 | 1632 | 1.8371 | 0.7582 |
| 1.9884 | 7.0 | 1904 | 1.7752 | 0.7701 |
| 1.8003 | 8.0 | 2176 | 1.7531 | 0.7674 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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