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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: flan-t5-small-codesearchnet-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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# flan-t5-small-codesearchnet-python |
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0764 |
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- Bleu: 0.0349 |
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- Rouge1: 0.6244 |
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- Rouge2: 0.6055 |
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- Avg Length: 16.9912 |
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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 | 0.0636 | 0.0364 | 0.6253 | 0.6076 | 17.029 | |
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| 5.5166 | 2.0 | 750 | 0.0553 | 0.0351 | 0.6259 | 0.6081 | 16.9996 | |
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| 0.0485 | 3.0 | 1125 | 0.0537 | 0.0351 | 0.6258 | 0.6083 | 16.99 | |
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| 0.0409 | 4.0 | 1500 | 0.0524 | 0.0351 | 0.6258 | 0.6082 | 16.9942 | |
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| 0.0409 | 5.0 | 1875 | 0.0524 | 0.0351 | 0.6261 | 0.6086 | 16.997 | |
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| 0.0345 | 6.0 | 2250 | 0.0526 | 0.0351 | 0.6258 | 0.6081 | 16.9936 | |
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| 0.0303 | 7.0 | 2625 | 0.0533 | 0.035 | 0.6254 | 0.6076 | 16.991 | |
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| 0.0256 | 8.0 | 3000 | 0.0566 | 0.035 | 0.6257 | 0.6074 | 16.9964 | |
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| 0.0256 | 9.0 | 3375 | 0.0592 | 0.0349 | 0.6253 | 0.6074 | 16.998 | |
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| 0.0205 | 10.0 | 3750 | 0.0612 | 0.0351 | 0.6255 | 0.6073 | 16.9932 | |
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| 0.0185 | 11.0 | 4125 | 0.0639 | 0.035 | 0.6257 | 0.6079 | 16.996 | |
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| 0.0157 | 12.0 | 4500 | 0.0698 | 0.035 | 0.625 | 0.6064 | 16.9944 | |
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| 0.0157 | 13.0 | 4875 | 0.0720 | 0.035 | 0.6246 | 0.6062 | 16.991 | |
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| 0.0131 | 14.0 | 5250 | 0.0745 | 0.035 | 0.6247 | 0.6062 | 16.9986 | |
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| 0.0128 | 15.0 | 5625 | 0.0764 | 0.0349 | 0.6244 | 0.6055 | 16.9912 | |
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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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