---
library_name: transformers
base_model: openai/clip-vit-base-patch32
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: clip-vit-base-patch32-finetuned-openai-clip-vit-base-patch32-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-patch32-finetuned-openai-clip-vit-base-patch32-emnist-letter

This model is a fine-tuned version of [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1524
- Accuracy: 0.9465

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.0859        | 0.9994 | 877  | 0.4055          | 0.8640   |
| 0.927         | 2.0    | 1755 | 0.3652          | 0.8782   |
| 0.83          | 2.9994 | 2632 | 0.2687          | 0.9066   |
| 0.7747        | 4.0    | 3510 | 0.2356          | 0.9189   |
| 0.7545        | 4.9994 | 4387 | 0.2147          | 0.9245   |
| 0.6461        | 6.0    | 5265 | 0.1889          | 0.9320   |
| 0.6457        | 6.9994 | 6142 | 0.1784          | 0.9354   |
| 0.6796        | 8.0    | 7020 | 0.1659          | 0.9412   |
| 0.5502        | 8.9994 | 7897 | 0.1548          | 0.9461   |
| 0.5797        | 9.9943 | 8770 | 0.1524          | 0.9465   |


### Framework versions

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