---
library_name: transformers
base_model: openai/clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: clip-vit-base-patch16-finetuned-openai-clip-vit-base-patch16-emnist-letter
  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. -->

# clip-vit-base-patch16-finetuned-openai-clip-vit-base-patch16-emnist-letter

This model is a fine-tuned version of [openai/clip-vit-base-patch16](https://huggingface.co/openai/clip-vit-base-patch16) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1460
- Accuracy: 0.9468

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.0535        | 0.9994 | 877  | 0.3616          | 0.8803   |
| 0.9258        | 2.0    | 1755 | 0.2692          | 0.9015   |
| 0.7331        | 2.9994 | 2632 | 0.2283          | 0.9207   |
| 0.7137        | 4.0    | 3510 | 0.1815          | 0.9353   |
| 0.6585        | 4.9994 | 4387 | 0.1889          | 0.9324   |
| 0.6366        | 6.0    | 5265 | 0.1688          | 0.9376   |
| 0.6284        | 6.9994 | 6142 | 0.1565          | 0.9424   |
| 0.5834        | 8.0    | 7020 | 0.1541          | 0.9433   |
| 0.5159        | 8.9994 | 7897 | 0.1425          | 0.9485   |
| 0.5233        | 9.9943 | 8770 | 0.1460          | 0.9468   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1