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--- |
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license: apache-2.0 |
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tags: |
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- CodeGPT-small-py |
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- hearthstone |
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metrics: |
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- bleu |
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- dvitel/codebleu |
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- exact_match |
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- chrf |
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datasets: |
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- dvitel/hearthstone |
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model-index: |
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- name: h0-1 |
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results: |
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- task: |
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type: text-generation |
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name: Python Code Synthesis |
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dataset: |
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type: dvitel/hearthstone |
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name: HearthStone |
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split: test |
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metrics: |
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- type: exact_match |
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value: 0.21212121212121213 |
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name: Exact Match |
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- type: bleu |
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value: 0.8954467480979604 |
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name: BLEU |
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- type: dvitel/codebleu |
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value: 0.6976253554171774 |
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name: CodeBLEU |
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- type: chrf |
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value: 91.42413429212283 |
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name: chrF |
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--- |
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# h0-1 |
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This model is a fine-tuned version of [microsoft/CodeGPT-small-py](https://huggingface.co/microsoft/CodeGPT-small-py) on [hearthstone](https://huggingface.co/datasets/dvitel/hearthstone) dataset. |
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[GitHub repo](https://github.com/dvitel/nlp-sem-parsing/blob/master/h0-1.py). |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3622 |
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- Exact Match: 0.1970 |
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- Bleu: 0.9193 |
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- Codebleu: 0.7686 |
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- Chrf: 93.5686 |
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## Model description |
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CodeGPT-small-py fine-tuned on HearthStone dataset for 200 epochs |
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## Intended uses & limitations |
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HearthStone card code synthesis. |
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## Training and evaluation data |
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See split of [hearthstone](https://huggingface.co/datasets/dvitel/hearthstone) dataset |
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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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 17 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- num_epochs: 200 |
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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 | Exact Match | Bleu | Codebleu | Chrf | |
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|:-------------:|:------:|:-----:|:---------------:|:-----------:|:------:|:--------:|:-------:| |
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| 0.2482 | 11.94 | 1600 | 0.2828 | 0.1364 | 0.9012 | 0.7012 | 92.2247 | |
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| 0.0203 | 23.88 | 3200 | 0.2968 | 0.1970 | 0.9114 | 0.7298 | 93.0236 | |
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| 0.0082 | 35.82 | 4800 | 0.3049 | 0.1970 | 0.9125 | 0.7480 | 93.1997 | |
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| 0.0049 | 47.76 | 6400 | 0.3190 | 0.1818 | 0.9125 | 0.7526 | 93.0967 | |
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| 0.0038 | 59.7 | 8000 | 0.3289 | 0.1818 | 0.9117 | 0.7348 | 93.1293 | |
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| 0.0024 | 71.64 | 9600 | 0.3358 | 0.1970 | 0.9142 | 0.7555 | 93.0747 | |
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| 0.0022 | 83.58 | 11200 | 0.3379 | 0.1970 | 0.9164 | 0.7642 | 93.2931 | |
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| 0.0013 | 95.52 | 12800 | 0.3444 | 0.2121 | 0.9189 | 0.7700 | 93.4456 | |
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| 0.0009 | 107.46 | 14400 | 0.3408 | 0.1970 | 0.9188 | 0.7655 | 93.4808 | |
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| 0.0006 | 119.4 | 16000 | 0.3522 | 0.1970 | 0.9177 | 0.7510 | 93.4061 | |
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| 0.0003 | 131.34 | 17600 | 0.3589 | 0.2121 | 0.9178 | 0.7614 | 93.3980 | |
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| 0.0002 | 143.28 | 19200 | 0.3562 | 0.2121 | 0.9179 | 0.7634 | 93.5130 | |
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| 0.0002 | 155.22 | 20800 | 0.3624 | 0.1970 | 0.9208 | 0.7699 | 93.6707 | |
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| 0.0001 | 167.16 | 22400 | 0.3608 | 0.1970 | 0.9193 | 0.7703 | 93.6082 | |
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| 0.0001 | 179.1 | 24000 | 0.3620 | 0.1970 | 0.9190 | 0.7667 | 93.5154 | |
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| 0.0001 | 191.04 | 25600 | 0.3622 | 0.1970 | 0.9193 | 0.7686 | 93.5686 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.13.0 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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