Model save
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README.md
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---
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library_name: transformers
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base_model: openai/clip-vit-large-patch14
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: clip-vit-large-patch14-finetuned-openai-clip-vit-large-patch14-emnist-letter
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# clip-vit-large-patch14-finetuned-openai-clip-vit-large-patch14-emnist-letter
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.1347
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- Accuracy: 0.9527
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:--------:|
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| 0.917 | 0.9994 | 877 | 0.3145 | 0.8863 |
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| 0.7921 | 2.0 | 1755 | 0.2430 | 0.9152 |
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| 0.7534 | 2.9994 | 2632 | 0.1897 | 0.9295 |
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| 0.6294 | 4.0 | 3510 | 0.1720 | 0.9373 |
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| 0.6219 | 4.9994 | 4387 | 0.1750 | 0.9390 |
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| 0.5749 | 6.0 | 5265 | 0.1486 | 0.9486 |
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| 0.5308 | 6.9994 | 6142 | 0.1431 | 0.9494 |
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| 0.5505 | 8.0 | 7020 | 0.1429 | 0.9499 |
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| 0.4938 | 8.9994 | 7897 | 0.1425 | 0.9496 |
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| 0.5342 | 9.9943 | 8770 | 0.1347 | 0.9527 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.0+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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