lmeninato/t5-small-codesearchnet-multilang-python-java

1---2license: apache-2.03tags:4- generated_from_trainer5metrics:6- bleu7- rouge8model-index:9- name: t5-small-codesearchnet-multilang-python-java10  results: []11---12 13<!-- This model card has been generated automatically according to the information the Trainer had access to. You14should probably proofread and complete it, then remove this comment. -->15 16# t5-small-codesearchnet-multilang-python-java17 18This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.19It achieves the following results on the evaluation set:20- Loss: 0.701521- Bleu: 0.004522- Rouge1: 0.219423- Rouge2: 0.074124- Avg Length: 15.997625 26## Model description27 28More information needed29 30## Intended uses & limitations31 32More information needed33 34## Training and evaluation data35 36More information needed37 38## Training procedure39 40### Training hyperparameters41 42The following hyperparameters were used during training:43- learning_rate: 5e-0544- train_batch_size: 845- eval_batch_size: 846- seed: 4247- gradient_accumulation_steps: 1048- total_train_batch_size: 8049- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0850- lr_scheduler_type: linear51- num_epochs: 1552 53### Training results54 55| Training Loss | Epoch | Step | Validation Loss | Bleu   | Rouge1 | Rouge2 | Avg Length |56|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:----------:|57| No log        | 1.0   | 375  | 0.9005          | 0.0013 | 0.1397 | 0.0334 | 16.3976    |58| 2.3568        | 2.0   | 750  | 0.8036          | 0.0023 | 0.1737 | 0.0526 | 15.8896    |59| 0.7576        | 3.0   | 1125 | 0.7584          | 0.0021 | 0.1856 | 0.0558 | 15.3102    |60| 0.6778        | 4.0   | 1500 | 0.7298          | 0.0024 | 0.1922 | 0.0597 | 15.3544    |61| 0.6778        | 5.0   | 1875 | 0.7114          | 0.0037 | 0.2114 | 0.0704 | 15.7588    |62| 0.6206        | 6.0   | 2250 | 0.6949          | 0.0039 | 0.2093 | 0.0729 | 15.8088    |63| 0.5856        | 7.0   | 2625 | 0.6927          | 0.0042 | 0.2143 | 0.0711 | 16.5838    |64| 0.5447        | 8.0   | 3000 | 0.6867          | 0.005  | 0.2151 | 0.0717 | 17.2174    |65| 0.5447        | 9.0   | 3375 | 0.6895          | 0.0043 | 0.2179 | 0.0736 | 16.1068    |66| 0.5117        | 10.0  | 3750 | 0.6876          | 0.0038 | 0.2229 | 0.0777 | 15.5094    |67| 0.4892        | 11.0  | 4125 | 0.6800          | 0.0047 | 0.2201 | 0.0783 | 16.6902    |68| 0.4629        | 12.0  | 4500 | 0.6903          | 0.0047 | 0.2203 | 0.0771 | 16.7658    |69| 0.4629        | 13.0  | 4875 | 0.6947          | 0.0056 | 0.227  | 0.0777 | 16.8108    |70| 0.4355        | 14.0  | 5250 | 0.6999          | 0.0027 | 0.2028 | 0.0715 | 15.6776    |71| 0.418         | 15.0  | 5625 | 0.7015          | 0.0045 | 0.2194 | 0.0741 | 15.9976    |72 73 74### Framework versions75 76- Transformers 4.28.177- Pytorch 2.0.0+cu11878- Datasets 2.12.079- Tokenizers 0.13.380