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  1. .gitattributes +6 -0
  2. README.md +79 -0
  3. checkpoint-2625/config.json +60 -0
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.gitattributes CHANGED
@@ -32,3 +32,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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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-python
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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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+ # t5-small-codesearchnet-python
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+
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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: 0.0785
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+ - Bleu: 0.035
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+ - Rouge1: 0.6257
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+ - Rouge2: 0.6078
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+ - Avg Length: 16.9954
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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: 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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+
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+ ### Training results
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+
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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 | 0.0801 | 0.0358 | 0.6174 | 0.6 | 17.1074 |
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+ | 1.6066 | 2.0 | 750 | 0.0674 | 0.036 | 0.6249 | 0.6068 | 17.0262 |
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+ | 0.0584 | 3.0 | 1125 | 0.0632 | 0.0351 | 0.6255 | 0.6075 | 16.9962 |
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+ | 0.0484 | 4.0 | 1500 | 0.0605 | 0.0351 | 0.6251 | 0.6071 | 17.003 |
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+ | 0.0484 | 5.0 | 1875 | 0.0596 | 0.035 | 0.6255 | 0.6075 | 17.0012 |
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+ | 0.0418 | 6.0 | 2250 | 0.0602 | 0.035 | 0.6258 | 0.608 | 16.9958 |
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+ | 0.0377 | 7.0 | 2625 | 0.0593 | 0.0351 | 0.6259 | 0.6079 | 17.0004 |
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+ | 0.033 | 8.0 | 3000 | 0.0618 | 0.035 | 0.6257 | 0.6078 | 17.0032 |
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+ | 0.033 | 9.0 | 3375 | 0.0637 | 0.035 | 0.6257 | 0.6078 | 16.998 |
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+ | 0.028 | 10.0 | 3750 | 0.0645 | 0.035 | 0.6257 | 0.6079 | 16.9984 |
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+ | 0.0255 | 11.0 | 4125 | 0.0650 | 0.035 | 0.6255 | 0.6078 | 17.0008 |
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+ | 0.0226 | 12.0 | 4500 | 0.0748 | 0.035 | 0.6254 | 0.6076 | 16.9976 |
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+ | 0.0226 | 13.0 | 4875 | 0.0714 | 0.035 | 0.6256 | 0.6079 | 16.9954 |
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+ | 0.019 | 14.0 | 5250 | 0.0747 | 0.0349 | 0.6253 | 0.6077 | 16.994 |
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+ | 0.0172 | 15.0 | 5625 | 0.0785 | 0.035 | 0.6257 | 0.6078 | 16.9954 |
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+
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+
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+ ### Framework versions
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+
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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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