muliple_choice
This model is a fine-tuned version of hfl/chinese-macbert-base on the clue dataset. It achieves the following results on the evaluation set:
- Loss: 1.3806
- Accuracy: 0.32
- Precision: 0.3720
- Recall: 0.3290
- F1: 0.3290
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
No log | 1.0 | 13 | 1.3806 | 0.32 | 0.3720 | 0.3290 | 0.3290 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Kique261/muliple_choice
Base model
hfl/chinese-macbert-base