---
library_name: transformers
base_model: openai/clip-vit-base-patch32
tags:
- image-classification
- generated_from_trainer
model-index:
- name: logo-matching-base
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# logo-matching-base

This model is a fine-tuned version of [openai/clip-vit-base-patch32](https://huggingface.co./openai/clip-vit-base-patch32) on the ellabettison/logo-matching dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0342
- eval_accuracy: 0.2435
- eval_runtime: 128.298
- eval_samples_per_second: 4.193
- eval_steps_per_second: 0.53
- epoch: 4.9362
- step: 232

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0