---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: asl_classification
  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_classification

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: 3.2012
- Accuracy: 0.0962

## 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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log        | 0.9231 | 6    | 3.1928          | 0.1058   |
| 2.9337        | 2.0    | 13   | 3.2067          | 0.0865   |
| 2.9337        | 2.9231 | 19   | 3.1925          | 0.1154   |
| 2.9273        | 4.0    | 26   | 3.1791          | 0.0769   |
| 2.9166        | 4.9231 | 32   | 3.1959          | 0.0962   |
| 2.9166        | 6.0    | 39   | 3.1797          | 0.0962   |
| 2.9078        | 6.9231 | 45   | 3.1835          | 0.1058   |
| 2.9157        | 8.0    | 52   | 3.1814          | 0.1154   |
| 2.9157        | 8.9231 | 58   | 3.1744          | 0.1058   |
| 2.9313        | 9.2308 | 60   | 3.1843          | 0.0962   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1