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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- bleu
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model-index:
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- name: h3
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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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# h3
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This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2782
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- Exact Match: 0.2879
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- Bleu: 0.9121
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- Codebleu: 0.7482
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- Ngram Match Score: 0.7504
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- Weighted Ngram Match Score: 0.7583
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- Syntax Match Score: 0.7673
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- Dataflow Match Score: 0.7169
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- Chrf: 93.1064
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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: 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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| 0.8612 | 11.94 | 1600 | 0.2725 | 0.0455 | 0.8477 | 0.6050 | 0.6229 | 0.6335 | 0.6203 | 0.5431 | 88.7010 |
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| 0.175 | 23.88 | 3200 | 0.2311 | 0.0909 | 0.8739 | 0.6304 | 0.6566 | 0.6656 | 0.6484 | 0.5508 | 90.7364 |
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| 0.1036 | 35.82 | 4800 | 0.2172 | 0.1818 | 0.8930 | 0.6905 | 0.6976 | 0.7062 | 0.7172 | 0.6409 | 91.9702 |
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| 0.0695 | 47.76 | 6400 | 0.2233 | 0.2424 | 0.8944 | 0.7017 | 0.7148 | 0.7232 | 0.7187 | 0.6499 | 92.0340 |
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| 0.0482 | 59.7 | 8000 | 0.2407 | 0.2879 | 0.9046 | 0.7301 | 0.7387 | 0.7456 | 0.7475 | 0.6885 | 92.6219 |
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| 0.0352 | 71.64 | 9600 | 0.2407 | 0.2424 | 0.9074 | 0.7255 | 0.7371 | 0.7448 | 0.7482 | 0.6718 | 92.8281 |
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| 0.0262 | 83.58 | 11200 | 0.2596 | 0.3030 | 0.9061 | 0.7445 | 0.7415 | 0.7500 | 0.7774 | 0.7091 | 92.6737 |
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| 0.0213 | 95.52 | 12800 | 0.2589 | 0.2879 | 0.9061 | 0.7308 | 0.7409 | 0.7488 | 0.7464 | 0.6873 | 92.7814 |
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| 0.0164 | 107.46 | 14400 | 0.2679 | 0.2879 | 0.9096 | 0.7452 | 0.7510 | 0.7592 | 0.7626 | 0.7079 | 92.9900 |
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| 0.0131 | 119.4 | 16000 | 0.2660 | 0.2879 | 0.9096 | 0.7447 | 0.7480 | 0.7564 | 0.7666 | 0.7079 | 93.0122 |
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| 0.0116 | 131.34 | 17600 | 0.2669 | 0.2727 | 0.9092 | 0.7463 | 0.7445 | 0.7529 | 0.7684 | 0.7194 | 92.9256 |
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| 0.0093 | 143.28 | 19200 | 0.2678 | 0.2879 | 0.9113 | 0.7531 | 0.7496 | 0.7581 | 0.7709 | 0.7336 | 93.0406 |
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| 0.0083 | 155.22 | 20800 | 0.2728 | 0.2879 | 0.9103 | 0.7407 | 0.7462 | 0.7540 | 0.7702 | 0.6924 | 92.9302 |
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| 0.0077 | 167.16 | 22400 | 0.2774 | 0.2879 | 0.9103 | 0.7449 | 0.7449 | 0.7532 | 0.7659 | 0.7156 | 92.9742 |
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| 0.0069 | 179.1 | 24000 | 0.2774 | 0.2879 | 0.9120 | 0.7396 | 0.7463 | 0.7539 | 0.7633 | 0.6950 | 93.1057 |
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| 0.0069 | 191.04 | 25600 | 0.2782 | 0.2879 | 0.9121 | 0.7482 | 0.7504 | 0.7583 | 0.7673 | 0.7169 | 93.1064 |
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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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