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furina_ary_corr_0.0001
Shijia/furina_ary_corr_0.0001
furina_ary_corr_0.0001 is a text classification model from Shijia. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- xlm-roberta
- Access
- Public
- Created
- Feb 16, 2024
- Updated
- Feb 16, 2024
- SHA
- 2d5656da
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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. -->
furina_ary_corr_0.0001
This model is a fine-tuned version of yihongLiu/furina on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0495
- Spearman Corr: nan
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Spearman Corr |
|---|---|---|---|---|
| No log | 0.9 | 200 | 0.0474 | nan |
| No log | 1.8 | 400 | 0.0471 | nan |
| 0.0493 | 2.7 | 600 | 0.0511 | nan |
| 0.0493 | 3.6 | 800 | 0.0477 | nan |
| 0.049 | 4.5 | 1000 | 0.0478 | nan |
| 0.049 | 5.41 | 1200 | 0.0474 | nan |
| 0.0489 | 6.31 | 1400 | 0.0470 | nan |
| 0.0489 | 7.21 | 1600 | 0.0467 | nan |
| 0.0488 | 8.11 | 1800 | 0.0495 | nan |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- Created
- Feb 16, 2024
- Updated
- Feb 16, 2024