|
--- |
|
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 |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/shark_meow_team/huggingface/runs/f4ofem3j) |
|
# aoi_clip_high_resolution_concate_fusin_gpt |
|
|
|
This model is a fine-tuned version of [OFA-Sys/chinese-clip-vit-base-patch16](https://huggingface.co./OFA-Sys/chinese-clip-vit-base-patch16) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 4.2052 |
|
- Accuracy: 0.0731 |
|
|
|
## 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 | |
|
|:-------------:|:-------:|:-----:|:---------------:|:--------:| |
|
| 2.3923 | 9.9872 | 3110 | 3.0972 | 0.0765 | |
|
| 2.1272 | 19.9743 | 6220 | 3.5858 | 0.0782 | |
|
| 1.9949 | 29.9615 | 9330 | 3.6033 | 0.0785 | |
|
| 1.957 | 39.9486 | 12440 | 3.7208 | 0.0769 | |
|
| 1.9313 | 49.9358 | 15550 | 3.8174 | 0.0759 | |
|
| 1.9255 | 59.9229 | 18660 | 3.9145 | 0.0748 | |
|
| 1.9179 | 69.9101 | 21770 | 4.0367 | 0.0746 | |
|
| 1.9133 | 79.8972 | 24880 | 4.0690 | 0.0740 | |
|
| 1.9102 | 89.8844 | 27990 | 4.1227 | 0.0737 | |
|
| 1.9084 | 99.8715 | 31100 | 4.2052 | 0.0734 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.3 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
