metadata
library_name: transformers
base_model: openai/clip-vit-base-patch32
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: clip-vit-base-patch32-finetuned-openai-clip-vit-base-patch32-emnist-letter
results: []
clip-vit-base-patch32-finetuned-openai-clip-vit-base-patch32-emnist-letter
This model is a fine-tuned version of openai/clip-vit-base-patch32 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1524
- Accuracy: 0.9465
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 |
|---|---|---|---|---|
| 1.0859 | 0.9994 | 877 | 0.4055 | 0.8640 |
| 0.927 | 2.0 | 1755 | 0.3652 | 0.8782 |
| 0.83 | 2.9994 | 2632 | 0.2687 | 0.9066 |
| 0.7747 | 4.0 | 3510 | 0.2356 | 0.9189 |
| 0.7545 | 4.9994 | 4387 | 0.2147 | 0.9245 |
| 0.6461 | 6.0 | 5265 | 0.1889 | 0.9320 |
| 0.6457 | 6.9994 | 6142 | 0.1784 | 0.9354 |
| 0.6796 | 8.0 | 7020 | 0.1659 | 0.9412 |
| 0.5502 | 8.9994 | 7897 | 0.1548 | 0.9461 |
| 0.5797 | 9.9943 | 8770 | 0.1524 | 0.9465 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1