metadata
base_model: OFA-Sys/chinese-clip-vit-base-patch16
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sentance_split_by_aoi_ocr_concate
results: []
sentance_split_by_aoi_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: 3.7314
- Accuracy: 0.0955
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 |
|---|---|---|---|---|
| 1.1802 | 5.9676 | 276 | 2.9987 | 0.0978 |
| 0.8645 | 11.9351 | 552 | 3.4895 | 0.0982 |
| 0.6579 | 17.9027 | 828 | 3.6032 | 0.1016 |
| 0.595 | 23.8703 | 1104 | 3.6243 | 0.0982 |
| 0.5518 | 29.8378 | 1380 | 3.6076 | 0.0975 |
| 0.5298 | 35.8054 | 1656 | 3.6513 | 0.0971 |
| 0.5155 | 41.7730 | 1932 | 3.5870 | 0.0970 |
| 0.5058 | 47.7405 | 2208 | 3.6555 | 0.0966 |
| 0.4935 | 53.7081 | 2484 | 3.6736 | 0.0960 |
| 0.4928 | 59.6757 | 2760 | 3.7314 | 0.0957 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1