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--- |
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base_model: uer/gpt2-chinese-cluecorpussmall |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: similar_question_generation |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# similar_question_generation |
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This model is a fine-tuned version of [uer/gpt2-chinese-cluecorpussmall](https://huggingface.co/uer/gpt2-chinese-cluecorpussmall) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0045 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 100.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 2.2108 | 0.21 | 1000 | 2.0433 | |
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| 2.047 | 0.42 | 2000 | 2.0138 | |
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| 1.9859 | 0.63 | 3000 | 1.9939 | |
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| 1.9471 | 0.84 | 4000 | 1.9953 | |
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| 1.8932 | 1.05 | 5000 | 2.0034 | |
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| 1.8224 | 1.26 | 6000 | 1.9962 | |
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| 1.8131 | 1.47 | 7000 | 1.9886 | |
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| 1.8007 | 1.69 | 8000 | 1.9881 | |
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| 1.7948 | 1.9 | 9000 | 1.9825 | |
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| 1.7314 | 2.11 | 10000 | 2.0049 | |
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| 1.6901 | 2.32 | 11000 | 2.0029 | |
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| 1.6941 | 2.53 | 12000 | 2.0012 | |
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| 1.6921 | 2.74 | 13000 | 2.0024 | |
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| 1.6917 | 2.95 | 14000 | 2.0045 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.0 |
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