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--- |
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base_model: OFA-Sys/chinese-clip-vit-base-patch16 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: sentance_split_by_time_gpt_concate_2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<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/cdver57p) |
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# sentance_split_by_time_gpt_concate_2 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.8914 |
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- Accuracy: 0.0782 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 25 |
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- eval_batch_size: 20 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 200 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 60.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:-----:|:---------------:|:--------:| |
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| 2.0864 | 5.9928 | 1866 | 2.9935 | 0.0803 | |
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| 1.9035 | 11.9855 | 3732 | 3.1629 | 0.0863 | |
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| 1.779 | 17.9783 | 5598 | 3.2064 | 0.0870 | |
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| 1.7158 | 23.9711 | 7464 | 3.4417 | 0.0854 | |
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| 1.6832 | 29.9639 | 9330 | 3.4988 | 0.0845 | |
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| 1.6554 | 35.9566 | 11196 | 3.5538 | 0.0833 | |
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| 1.6498 | 41.9494 | 13062 | 3.6819 | 0.0819 | |
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| 1.6335 | 47.9422 | 14928 | 3.7696 | 0.0809 | |
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| 1.6339 | 53.9350 | 16794 | 3.8098 | 0.0799 | |
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| 1.6264 | 59.9277 | 18660 | 3.8914 | 0.0789 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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