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--- |
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tags: |
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- Luc bat poem |
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- GPT2 |
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- Causal-lm |
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model-index: |
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- name: PoetGPT_Vietnamese |
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results: [] |
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language: |
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- vi |
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widget: |
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- text: "<|startoftext|>ngày xuân" |
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example_title: "ngày xuân" |
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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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# Lục Bát AI Poet |
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## How to generation with prompt? |
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``` |
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Type: |
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<|startoftext|> + your_prompt |
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Examples: |
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<|startoftext|>ngày xuân |
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``` |
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## Usage: |
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``` |
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import torch |
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from transformers import GPT2Tokenizer, GPT2LMHeadModel |
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tokenizer = GPT2Tokenizer.from_pretrained('luanngo/PoetGPT') |
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model = GPT2LMHeadModel.from_pretrained('luanngo/PoetGPT') |
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prompt = "<|startoftext|>" + "ngày xuân" |
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input_ids = tokenizer.encode(prompt.lower(), return_tensors='pt') |
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max_length = 100 |
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outputs = model.generate(input_ids, |
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do_sample=True, |
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max_length=max_length, |
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top_p=0.95, |
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temperature=1.0, |
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repetition_penalty=10.0, |
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num_beams=5, |
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early_stopping=True, |
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num_return_sequences=3) |
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for i, output in enumerate(outputs): |
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print(">> Generated text {}\n\n{}".format(i+1, |
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tokenizer.decode(output.tolist()))) |
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print('\n---') |
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``` |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-4 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 37 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 128 |
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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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- num_epochs: 30 |
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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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| 2.6633 | 1.0 | 704 | 2.6718 | |
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| 2.5567 | 2.0 | 1408 | 2.5756 | |
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| 2.4885 | 3.0 | 2112 | 2.5283 | |
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| 2.3552 | 4.0 | 2816 | 2.4395 | |
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| 2.3084 | 5.0 | 3520 | 2.3811 | |
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| 2.2587 | 6.0 | 4224 | 2.3699 | |
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| 2.1938 | 7.0 | 4928 | 2.3470 | |
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| 2.1491 | 8.0 | 5632 | 2.3225 | |
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| 2.0623 | 9.0 | 6336 | 2.3276 | |
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| 2.0672 | 10.0 | 7040 | 2.3301 | |
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| 2.0293 | 11.0 | 7744 | 2.3186 | |
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| 1.9694 | 12.0 | 8448 | 2.3331 | |
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| 1.8658 | 13.0 | 9152 | 2.3565 | |
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| 1.8558 | 14.0 | 9856 | 2.3592 | |
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### Framework versions |
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- Transformers 4.22.2 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.6.1 |
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- Tokenizers 0.12.1 |
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