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--- |
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license: apache-2.0 |
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base_model: Salesforce/codet5-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- code_x_glue_tc_text_to_code |
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metrics: |
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- rouge |
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model-index: |
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- name: codet5-small-java-v1-text-to-code |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: code_x_glue_tc_text_to_code |
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type: code_x_glue_tc_text_to_code |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 57.1969 |
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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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# codet5-small-java-v1-text-to-code |
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This model is a fine-tuned version of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small) on the code_x_glue_tc_text_to_code dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7705 |
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- Rouge1: 57.1969 |
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- Rouge2: 40.0098 |
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- Rougel: 55.326 |
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- Rougelsum: 56.119 |
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- Gen Len: 16.8335 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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- num_epochs: 4 |
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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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| 0.7434 | 1.0 | 6250 | 0.8148 | 55.9045 | 38.592 | 54.0278 | 54.7633 | 16.796 | |
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| 0.6708 | 2.0 | 12500 | 0.7868 | 56.3354 | 38.9843 | 54.5278 | 55.2197 | 16.751 | |
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| 0.6309 | 3.0 | 18750 | 0.7741 | 56.9883 | 39.8626 | 55.1321 | 55.9173 | 16.8495 | |
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| 0.6262 | 4.0 | 25000 | 0.7705 | 57.1969 | 40.0098 | 55.326 | 56.119 | 16.8335 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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