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--- |
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license: apache-2.0 |
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tags: |
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- distigpt2 |
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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 |
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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: 0.19696969696969696 |
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name: Exact Match |
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- type: bleu |
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value: 0.8881228393983 |
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name: BLEU |
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- type: dvitel/codebleu |
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value: 0.6764180663401291 |
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name: CodeBLEU |
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- type: chrf |
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value: 90.6099642899634 |
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name: chrF |
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--- |
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# h0 |
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This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) 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.py). |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3117 |
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- Exact Match: 0.1970 |
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- Bleu: 0.9085 |
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- Codebleu: 0.7341 |
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- Ngram Match Score: 0.7211 |
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- Weighted Ngram Match Score: 0.7299 |
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- Syntax Match Score: 0.7536 |
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- Dataflow Match Score: 0.7317 |
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- Chrf: 92.8689 |
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## Model description |
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DistilGPT2 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 | Ngram Match Score | Weighted Ngram Match Score | Syntax Match Score | Dataflow Match Score | Chrf | |
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|:-------------:|:------:|:-----:|:---------------:|:-----------:|:------:|:--------:|:-----------------:|:--------------------------:|:------------------:|:--------------------:|:-------:| |
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| 0.543 | 11.94 | 1600 | 0.2701 | 0.0152 | 0.8552 | 0.6144 | 0.6027 | 0.6136 | 0.6431 | 0.5982 | 89.0280 | |
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| 0.1459 | 23.88 | 3200 | 0.2408 | 0.0909 | 0.8841 | 0.6733 | 0.6610 | 0.6719 | 0.7210 | 0.6393 | 91.2517 | |
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| 0.0801 | 35.82 | 4800 | 0.2498 | 0.1515 | 0.8966 | 0.6999 | 0.6954 | 0.7054 | 0.7326 | 0.6662 | 92.1356 | |
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| 0.0498 | 47.76 | 6400 | 0.2569 | 0.1818 | 0.9012 | 0.7015 | 0.7022 | 0.7114 | 0.7428 | 0.6496 | 92.4668 | |
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| 0.0323 | 59.7 | 8000 | 0.2732 | 0.1667 | 0.9044 | 0.7241 | 0.7025 | 0.7123 | 0.7551 | 0.7266 | 92.5429 | |
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| 0.0214 | 71.64 | 9600 | 0.2896 | 0.1667 | 0.9034 | 0.7228 | 0.7101 | 0.7195 | 0.7670 | 0.6945 | 92.4258 | |
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| 0.015 | 83.58 | 11200 | 0.2870 | 0.1667 | 0.9046 | 0.7292 | 0.7137 | 0.7228 | 0.7667 | 0.7137 | 92.5979 | |
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| 0.0121 | 95.52 | 12800 | 0.2907 | 0.1667 | 0.9075 | 0.7287 | 0.7198 | 0.7297 | 0.7696 | 0.6958 | 92.7074 | |
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| 0.0093 | 107.46 | 14400 | 0.2976 | 0.1667 | 0.9073 | 0.7365 | 0.7134 | 0.7238 | 0.7732 | 0.7356 | 92.8347 | |
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| 0.0073 | 119.4 | 16000 | 0.3037 | 0.1818 | 0.9085 | 0.7326 | 0.7154 | 0.7241 | 0.7529 | 0.7381 | 92.8343 | |
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| 0.006 | 131.34 | 17600 | 0.3047 | 0.1970 | 0.9104 | 0.7410 | 0.7230 | 0.7312 | 0.7667 | 0.7433 | 92.8286 | |
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| 0.005 | 143.28 | 19200 | 0.3080 | 0.1970 | 0.9088 | 0.7377 | 0.7232 | 0.7316 | 0.7746 | 0.7214 | 92.8035 | |
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| 0.0044 | 155.22 | 20800 | 0.3071 | 0.1970 | 0.9076 | 0.7343 | 0.7196 | 0.7283 | 0.7783 | 0.7112 | 92.7742 | |
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| 0.004 | 167.16 | 22400 | 0.3097 | 0.1970 | 0.9082 | 0.7440 | 0.7236 | 0.7334 | 0.7601 | 0.7587 | 92.8117 | |
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| 0.0035 | 179.1 | 24000 | 0.3111 | 0.1970 | 0.9080 | 0.7355 | 0.7204 | 0.7295 | 0.7616 | 0.7304 | 92.7990 | |
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| 0.0036 | 191.04 | 25600 | 0.3117 | 0.1970 | 0.9085 | 0.7341 | 0.7211 | 0.7299 | 0.7536 | 0.7317 | 92.8689 | |
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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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