---
library_name: transformers
base_model: openai/clip-vit-large-patch14-336
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: clip-vit-large-patch14-336-finetuned-openai-clip-vit-large-patch14-336-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-patch14-336-finetuned-openai-clip-vit-large-patch14-336-emnist-letter

This model is a fine-tuned version of [openai/clip-vit-large-patch14-336](https://huggingface.co/openai/clip-vit-large-patch14-336) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1417
- Accuracy: 0.9489

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8898        | 0.9994 | 877  | 0.3490          | 0.8834   |
| 0.8457        | 2.0    | 1755 | 0.2191          | 0.9224   |
| 0.7238        | 2.9994 | 2632 | 0.2113          | 0.9263   |
| 0.6685        | 4.0    | 3510 | 0.1838          | 0.9348   |
| 0.6236        | 4.9994 | 4387 | 0.2217          | 0.9205   |
| 0.6011        | 6.0    | 5265 | 0.1732          | 0.9386   |
| 0.6129        | 6.9994 | 6142 | 0.1582          | 0.9419   |
| 0.5606        | 8.0    | 7020 | 0.1478          | 0.9465   |
| 0.5136        | 8.9994 | 7897 | 0.1488          | 0.9458   |
| 0.4659        | 9.9943 | 8770 | 0.1417          | 0.9489   |


### Framework versions

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