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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: h2
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+ results: []
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+ ---
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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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+
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+ # h2
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+
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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: 2.5771
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+ - Exact Match: 0.0
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+ - Bleu: 0.6619
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+ - Codebleu: 0.5374
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+ - Ngram Match Score: 0.4051
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+ - Weighted Ngram Match Score: 0.4298
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+ - Syntax Match Score: 0.5605
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+ - Dataflow Match Score: 0.7541
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+ - Chrf: 73.9625
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+ | 1.2052 | 11.94 | 1600 | 1.2887 | 0.0 | 0.6340 | 0.4427 | 0.3384 | 0.3614 | 0.5263 | 0.5446 | 70.8004 |
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+ | 0.3227 | 23.88 | 3200 | 1.4484 | 0.0 | 0.6575 | 0.5050 | 0.3767 | 0.3995 | 0.5955 | 0.6485 | 72.9553 |
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+ | 0.205 | 35.82 | 4800 | 1.6392 | 0.0 | 0.6598 | 0.5174 | 0.3788 | 0.4022 | 0.5821 | 0.7063 | 73.2766 |
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+ | 0.1392 | 47.76 | 6400 | 1.8219 | 0.0 | 0.6584 | 0.5279 | 0.3922 | 0.4159 | 0.5742 | 0.7294 | 73.5022 |
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+ | 0.0979 | 59.7 | 8000 | 1.9416 | 0.0 | 0.6635 | 0.5305 | 0.4012 | 0.4248 | 0.5699 | 0.7261 | 73.8081 |
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+ | 0.0694 | 71.64 | 9600 | 2.1793 | 0.0 | 0.6593 | 0.5400 | 0.4027 | 0.4271 | 0.5562 | 0.7739 | 73.6746 |
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+ | 0.0512 | 83.58 | 11200 | 2.2547 | 0.0 | 0.6585 | 0.5433 | 0.4040 | 0.4283 | 0.5486 | 0.7921 | 73.7670 |
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+ | 0.0399 | 95.52 | 12800 | 2.3037 | 0.0 | 0.6585 | 0.5354 | 0.4040 | 0.4282 | 0.5454 | 0.7640 | 73.7431 |
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+ | 0.0316 | 107.46 | 14400 | 2.4113 | 0.0 | 0.6577 | 0.5294 | 0.4006 | 0.4257 | 0.5504 | 0.7409 | 73.7004 |
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+ | 0.0254 | 119.4 | 16000 | 2.4407 | 0.0 | 0.6607 | 0.5412 | 0.4041 | 0.4285 | 0.5598 | 0.7723 | 73.8828 |
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+ | 0.0208 | 131.34 | 17600 | 2.4993 | 0.0 | 0.6637 | 0.5330 | 0.4042 | 0.4286 | 0.5684 | 0.7310 | 74.1760 |
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+ | 0.0176 | 143.28 | 19200 | 2.5138 | 0.0 | 0.6627 | 0.5434 | 0.4050 | 0.4295 | 0.5620 | 0.7772 | 74.0546 |
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+ | 0.0158 | 155.22 | 20800 | 2.5589 | 0.0 | 0.6616 | 0.5347 | 0.4044 | 0.4291 | 0.5512 | 0.7541 | 73.9516 |
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+ | 0.0147 | 167.16 | 22400 | 2.5554 | 0.0 | 0.6620 | 0.5354 | 0.4049 | 0.4295 | 0.5630 | 0.7442 | 73.9461 |
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+ | 0.0134 | 179.1 | 24000 | 2.5696 | 0.0 | 0.6607 | 0.5395 | 0.4046 | 0.4293 | 0.5602 | 0.7640 | 73.8383 |
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+ | 0.0135 | 191.04 | 25600 | 2.5771 | 0.0 | 0.6619 | 0.5374 | 0.4051 | 0.4298 | 0.5605 | 0.7541 | 73.9625 |
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+
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+
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+ ### Framework versions
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+
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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