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sentance_split_by_aoi_gpt_crossAttention
sharkMeow/sentance_split_by_aoi_gpt_crossAttention
sentance_split_by_aoi_gpt_crossAttention 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 8, 2024
- SHA
- e194c216
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_aoi_gpt_crossAttention
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: 4.1585
- Accuracy: 0.0675
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 |
|---|---|---|---|---|
| 1.2577 | 5.9676 | 276 | 2.9735 | 0.0719 |
| 1.194 | 11.9351 | 552 | 2.9341 | 0.0719 |
| 1.1008 | 17.9027 | 828 | 3.0206 | 0.0690 |
| 1.0173 | 23.8703 | 1104 | 3.2514 | 0.0667 |
| 0.9404 | 29.8378 | 1380 | 3.4461 | 0.0679 |
| 0.8841 | 35.8054 | 1656 | 3.6906 | 0.0698 |
| 0.8364 | 41.7730 | 1932 | 3.8565 | 0.0702 |
| 0.8136 | 47.7405 | 2208 | 4.0121 | 0.0697 |
| 0.7757 | 53.7081 | 2484 | 4.0667 | 0.0686 |
| 0.766 | 59.6757 | 2760 | 4.1585 | 0.0680 |
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 8, 2024