metadata
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: aoi_clip_high_resolution_concate_fusin_crop_each_text_256
results: []
aoi_clip_high_resolution_concate_fusin_crop_each_text_256
This model is a fine-tuned version of OFA-Sys/chinese-clip-vit-base-patch16 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.5401
- Accuracy: 0.0635
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: 1e-05
- train_batch_size: 20
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 200
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.7271 | 5.9821 | 1602 | 3.0070 | 0.0789 |
| 1.6271 | 11.9642 | 3204 | 3.1514 | 0.0732 |
| 1.552 | 17.9462 | 4806 | 3.1511 | 0.0705 |
| 1.5094 | 23.9283 | 6408 | 3.3706 | 0.0684 |
| 1.484 | 29.9104 | 8010 | 3.4197 | 0.0672 |
| 1.4683 | 35.8925 | 9612 | 3.5270 | 0.0666 |
| 1.4567 | 41.8745 | 11214 | 3.4933 | 0.0658 |
| 1.4541 | 47.8566 | 12816 | 3.4874 | 0.0653 |
| 1.4539 | 53.8387 | 14418 | 3.5305 | 0.0646 |
| 1.452 | 59.8208 | 16020 | 3.5401 | 0.0640 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1