---
library_name: transformers
license: apache-2.0
base_model: google/siglip2-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: siglip2-finetuned-marathi-sign-language
  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. -->

# siglip2-finetuned-marathi-sign-language

This model is a fine-tuned version of [google/siglip2-base-patch16-224](https://huggingface.co/google/siglip2-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0006
- Model Preparation Time: 0.0057
- Accuracy: 0.9997

## 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: 2e-06
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|
| 1.4439        | 1.0   | 940  | 0.0090          | 0.0057                 | 0.9980   |
| 0.0052        | 2.0   | 1880 | 0.0035          | 0.0057                 | 0.9993   |
| 0.0031        | 3.0   | 2820 | 0.0016          | 0.0057                 | 0.9997   |
| 0.001         | 4.0   | 3760 | 0.0010          | 0.0057                 | 0.9997   |
| 0.0007        | 5.0   | 4700 | 0.0013          | 0.0057                 | 0.9997   |
| 0.0005        | 6.0   | 5640 | 0.0006          | 0.0057                 | 0.9997   |


### Framework versions

- Transformers 4.52.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1