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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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- rouge |
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model-index: |
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- name: t5-small-codesearchnet-multilang-python |
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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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# t5-small-codesearchnet-multilang-python |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8169 |
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- Bleu: 0.0012 |
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- Rouge1: 0.1986 |
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- Rouge2: 0.0594 |
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- Avg Length: 14.004 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 10 |
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- total_train_batch_size: 80 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge1 | Rouge2 | Avg Length | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:----------:| |
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| No log | 1.0 | 375 | 0.9943 | 0.0003 | 0.1637 | 0.0365 | 13.785 | |
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| 2.445 | 2.0 | 750 | 0.8991 | 0.0002 | 0.171 | 0.041 | 13.0266 | |
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| 0.8324 | 3.0 | 1125 | 0.8509 | 0.001 | 0.1931 | 0.0499 | 14.9474 | |
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| 0.7567 | 4.0 | 1500 | 0.8184 | 0.0015 | 0.2019 | 0.0561 | 14.9598 | |
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| 0.7567 | 5.0 | 1875 | 0.8002 | 0.0016 | 0.2097 | 0.0608 | 14.496 | |
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| 0.6947 | 6.0 | 2250 | 0.7793 | 0.0016 | 0.2138 | 0.0631 | 14.6502 | |
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| 0.658 | 7.0 | 2625 | 0.7721 | 0.0018 | 0.2104 | 0.0617 | 15.2 | |
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| 0.6186 | 8.0 | 3000 | 0.7669 | 0.0023 | 0.2175 | 0.0642 | 15.7472 | |
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| 0.6186 | 9.0 | 3375 | 0.7792 | 0.0027 | 0.2218 | 0.0664 | 15.862 | |
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| 0.58 | 10.0 | 3750 | 0.7629 | 0.0005 | 0.1985 | 0.0591 | 12.0968 | |
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| 0.5533 | 11.0 | 4125 | 0.7826 | 0.0027 | 0.2126 | 0.0631 | 16.9146 | |
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| 0.5279 | 12.0 | 4500 | 0.7907 | 0.0025 | 0.2144 | 0.0626 | 16.656 | |
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| 0.5279 | 13.0 | 4875 | 0.7827 | 0.0007 | 0.2019 | 0.0606 | 12.4734 | |
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| 0.4964 | 14.0 | 5250 | 0.7933 | 0.0023 | 0.2204 | 0.0674 | 15.344 | |
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| 0.4803 | 15.0 | 5625 | 0.8169 | 0.0012 | 0.1986 | 0.0594 | 14.004 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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