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

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: 2.1829
- Accuracy: 0.2367

## 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: 30
- total_train_batch_size: 960
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.2886        | 0.9953 | 56   | 2.2661          | 0.157    |
| 2.2153        | 1.9905 | 112  | 2.2004          | 0.1945   |
| 2.1981        | 2.9858 | 168  | 2.1829          | 0.2367   |


### Framework versions

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