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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: my_isl_model
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.7283950617283951
---
<!-- 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. -->
# my_isl_model
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9092
- Accuracy: 0.7284
## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.1292 | 0.96 | 11 | 3.0256 | 0.2593 |
| 2.9426 | 2.0 | 23 | 2.7796 | 0.2716 |
| 2.706 | 2.96 | 34 | 2.5462 | 0.4321 |
| 2.5389 | 4.0 | 46 | 2.4454 | 0.4568 |
| 2.3638 | 4.96 | 57 | 2.2169 | 0.6914 |
| 2.1862 | 6.0 | 69 | 2.1349 | 0.6296 |
| 2.0459 | 6.96 | 80 | 2.1135 | 0.6049 |
| 1.9912 | 8.0 | 92 | 1.9757 | 0.7531 |
| 1.9504 | 8.96 | 103 | 1.9073 | 0.7407 |
| 1.942 | 9.57 | 110 | 1.9092 | 0.7284 |
### Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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