xlnet-base
This model is a fine-tuned version of hfl/chinese-xlnet-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.7194
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 8.1116 | 0.11 | 500 | 6.8678 |
| 6.8507 | 0.22 | 1000 | 6.7533 |
| 6.7394 | 0.34 | 1500 | 6.7035 |
| 6.6534 | 0.45 | 2000 | 6.6033 |
| 6.5451 | 0.56 | 2500 | 6.4870 |
| 6.4314 | 0.67 | 3000 | 6.3461 |
| 6.2783 | 0.78 | 3500 | 6.2090 |
| 6.1681 | 0.9 | 4000 | 6.0913 |
| 6.0757 | 1.01 | 4500 | 5.9937 |
| 5.9735 | 1.12 | 5000 | 5.9321 |
| 5.9025 | 1.23 | 5500 | 5.8552 |
| 5.8424 | 1.34 | 6000 | 5.8166 |
| 5.804 | 1.45 | 6500 | 5.7849 |
| 5.7535 | 1.57 | 7000 | 5.7420 |
| 5.7674 | 1.68 | 7500 | 5.7311 |
| 5.7613 | 1.79 | 8000 | 5.7269 |
| 5.7322 | 1.9 | 8500 | 5.7194 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
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Model tree for Xiugapurin/xlnet-base
Base model
hfl/chinese-xlnet-base