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- transformers
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license: apache-2.0
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metrics:
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- exact_match
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- bleu
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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: h0
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results: []
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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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# h0
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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: 0.3117
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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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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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| 0.543 | 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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