| | --- |
| | base_model: OFA-Sys/chinese-clip-vit-base-patch16 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: sentance_split_by_time_gpt_None |
| | 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/o5nhn3mn) |
| | # sentance_split_by_time_gpt_None |
| | |
| | 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: 2.7000 |
| | - Accuracy: 0.2724 |
| | |
| | ## 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 | |
| | |:-------------:|:-------:|:-----:|:---------------:|:--------:| |
| | | 2.0366 | 5.9928 | 1866 | 2.3592 | 0.3213 | |
| | | 1.8711 | 11.9855 | 3732 | 2.4432 | 0.3110 | |
| | | 1.7987 | 17.9783 | 5598 | 2.5182 | 0.3014 | |
| | | 1.7585 | 23.9711 | 7464 | 2.5565 | 0.2937 | |
| | | 1.7381 | 29.9639 | 9330 | 2.5971 | 0.2895 | |
| | | 1.7139 | 35.9566 | 11196 | 2.6406 | 0.2849 | |
| | | 1.7102 | 41.9494 | 13062 | 2.6703 | 0.2815 | |
| | | 1.6951 | 47.9422 | 14928 | 2.6753 | 0.2783 | |
| | | 1.6954 | 53.9350 | 16794 | 2.6847 | 0.2761 | |
| | | 1.6888 | 59.9277 | 18660 | 2.7000 | 0.2741 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.42.3 |
| | - Pytorch 2.3.1+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| |
|
