metadata
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sentance_split_by_time_ocr_concate
results: []
sentance_split_by_time_ocr_concate
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: 3.7882
- Accuracy: 0.0651
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: 25
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 8
- 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 |
|---|---|---|---|---|
| 2.0902 | 5.9928 | 1866 | 3.0755 | 0.0687 |
| 1.8876 | 11.9855 | 3732 | 3.2740 | 0.0669 |
| 1.763 | 17.9783 | 5598 | 3.2469 | 0.0681 |
| 1.7048 | 23.9711 | 7464 | 3.4242 | 0.0677 |
| 1.6776 | 29.9639 | 9330 | 3.4987 | 0.0674 |
| 1.6518 | 35.9566 | 11196 | 3.5633 | 0.0675 |
| 1.6471 | 41.9494 | 13062 | 3.6389 | 0.0668 |
| 1.6319 | 47.9422 | 14928 | 3.6843 | 0.0663 |
| 1.6325 | 53.9350 | 16794 | 3.7068 | 0.0658 |
| 1.6255 | 59.9277 | 18660 | 3.7882 | 0.0654 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1