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sentance_split_by_time_gpt_None
sharkMeow/sentance_split_by_time_gpt_None
sentance_split_by_time_gpt_None is a machine learning model from sharkMeow. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Model type
- chinese_clip
- Access
- Public
- Created
- Oct 8, 2024
- Updated
- Oct 9, 2024
- SHA
- e3414e22
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
sentance_split_by_time_gpt_None
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: 2.7000
- 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
- Type
- chinese_clip
- Created
- Oct 8, 2024
- Updated
- Oct 9, 2024