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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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- rouge
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- bleu
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model-index:
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- name: Salesforce-codet5-small-CodeXGLUE-CONCODE-test
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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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# Salesforce-codet5-small-CodeXGLUE-CONCODE-test
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This model is a fine-tuned version of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8508
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- Exact Match: 0.156
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- Rouge1: 0.5559
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- Rouge2: 0.3857
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- Rougel: 0.5378
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- Rougelsum: 0.5465
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- Bleu: 0.1246
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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: 0.001
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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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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- lr_scheduler_warmup_ratio: 0.05
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- num_epochs: 1
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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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu |
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|:-------------:|:-----:|:----:|:---------------:|:-----------:|:------:|:------:|:------:|:---------:|:------:|
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| 1.3563 | 0.16 | 500 | 1.1652 | 0.1115 | 0.5098 | 0.3191 | 0.4915 | 0.4982 | 0.1088 |
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| 0.9656 | 0.32 | 1000 | 1.0435 | 0.1245 | 0.5246 | 0.3444 | 0.5075 | 0.5145 | 0.1164 |
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| 0.8627 | 0.48 | 1500 | 0.9851 | 0.121 | 0.5275 | 0.3420 | 0.5074 | 0.5154 | 0.1132 |
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| 0.7718 | 0.64 | 2000 | 0.9288 | 0.1385 | 0.5334 | 0.3589 | 0.5174 | 0.5242 | 0.1206 |
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| 0.7237 | 0.8 | 2500 | 0.8867 | 0.1495 | 0.5505 | 0.3762 | 0.5328 | 0.5406 | 0.1208 |
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| 0.6812 | 0.96 | 3000 | 0.8508 | 0.156 | 0.5559 | 0.3857 | 0.5378 | 0.5465 | 0.1246 |
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### Framework versions
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- Transformers 4.27.1
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- Pytorch 1.12.1+cu113
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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