asl_classification / README.md
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---
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