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_gpt_random_sampler
results: []
aoi_clip_high_resolution_concate_fusin_gpt_random_sampler
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: 2.9963
- Accuracy: 0.0500
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: 40
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 200
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0008 | 9.9872 | 3110 | 3.0008 | 0.0500 |
| 0.0007 | 19.9743 | 6220 | 2.9971 | 0.0501 |
| 0.0007 | 29.9615 | 9330 | 2.9971 | 0.0501 |
| 0.0007 | 39.9486 | 12440 | 2.9988 | 0.0500 |
| 0.0007 | 49.9358 | 15550 | 2.9968 | 0.0499 |
| 0.0007 | 59.9229 | 18660 | 2.9966 | 0.0502 |
| 0.0007 | 69.9101 | 21770 | 2.9961 | 0.0503 |
| 0.0007 | 79.8972 | 24880 | 2.9967 | 0.0503 |
| 0.0007 | 89.8844 | 27990 | 2.9966 | 0.0503 |
| 0.0007 | 99.8715 | 31100 | 2.9963 | 0.0502 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1