---
library_name: transformers
base_model: openai/clip-vit-large-patch14
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: clip-vit-large-patch14-finetuned-openai-clip-vit-large-patch14-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-large-patch14-finetuned-openai-clip-vit-large-patch14-emnist-letter

This model is a fine-tuned version of [openai/clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1347
- Accuracy: 0.9527

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.917         | 0.9994 | 877  | 0.3145          | 0.8863   |
| 0.7921        | 2.0    | 1755 | 0.2430          | 0.9152   |
| 0.7534        | 2.9994 | 2632 | 0.1897          | 0.9295   |
| 0.6294        | 4.0    | 3510 | 0.1720          | 0.9373   |
| 0.6219        | 4.9994 | 4387 | 0.1750          | 0.9390   |
| 0.5749        | 6.0    | 5265 | 0.1486          | 0.9486   |
| 0.5308        | 6.9994 | 6142 | 0.1431          | 0.9494   |
| 0.5505        | 8.0    | 7020 | 0.1429          | 0.9499   |
| 0.4938        | 8.9994 | 7897 | 0.1425          | 0.9496   |
| 0.5342        | 9.9943 | 8770 | 0.1347          | 0.9527   |


### Framework versions

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