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---
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