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