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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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<!-- 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-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: 0.7802 |
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- Bleu: 0.0027 |
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- Rouge1: 0.2097 |
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- Rouge2: 0.0628 |
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- Avg Length: 15.7496 |
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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 | 0.9665 | 0.0004 | 0.1696 | 0.0384 | 14.1472 | |
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| 2.0677 | 2.0 | 750 | 0.8740 | 0.0004 | 0.1758 | 0.0428 | 13.38 | |
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| 0.8314 | 3.0 | 1125 | 0.8281 | 0.001 | 0.1925 | 0.0505 | 14.8026 | |
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| 0.7563 | 4.0 | 1500 | 0.7996 | 0.0017 | 0.2033 | 0.0582 | 14.9606 | |
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| 0.7563 | 5.0 | 1875 | 0.7780 | 0.0022 | 0.2117 | 0.0607 | 14.9434 | |
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| 0.6959 | 6.0 | 2250 | 0.7587 | 0.002 | 0.2135 | 0.0621 | 14.6926 | |
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| 0.6591 | 7.0 | 2625 | 0.7545 | 0.002 | 0.2073 | 0.0605 | 15.2818 | |
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| 0.6205 | 8.0 | 3000 | 0.7472 | 0.0024 | 0.2187 | 0.0674 | 15.051 | |
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| 0.6205 | 9.0 | 3375 | 0.7506 | 0.0031 | 0.2266 | 0.0696 | 15.6286 | |
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| 0.5822 | 10.0 | 3750 | 0.7449 | 0.001 | 0.206 | 0.063 | 13.1462 | |
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| 0.5553 | 11.0 | 4125 | 0.7573 | 0.0027 | 0.2148 | 0.0647 | 16.4076 | |
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| 0.5295 | 12.0 | 4500 | 0.7677 | 0.0026 | 0.2185 | 0.0658 | 15.8986 | |
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| 0.5295 | 13.0 | 4875 | 0.7595 | 0.0009 | 0.2052 | 0.0618 | 12.3528 | |
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| 0.4977 | 14.0 | 5250 | 0.7766 | 0.0035 | 0.2177 | 0.0636 | 16.6706 | |
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| 0.4818 | 15.0 | 5625 | 0.7802 | 0.0027 | 0.2097 | 0.0628 | 15.7496 | |
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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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