anithra/code-assistant-py-java2

1---2library_name: transformers3license: apache-2.04base_model: Salesforce/codet5-small5tags:6- generated_from_trainer7model-index:8- name: code-assistant-py-java29  results: []10---11 12<!-- This model card has been generated automatically according to the information the Trainer had access to. You13should probably proofread and complete it, then remove this comment. -->14 15# code-assistant-py-java216 17This model is a fine-tuned version of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small) on an unknown dataset.18It achieves the following results on the evaluation set:19- Loss: 0.291420 21## Model description22 23More information needed24 25## Intended uses & limitations26 27More information needed28 29## Training and evaluation data30 31More information needed32 33## Training procedure34 35### Training hyperparameters36 37The following hyperparameters were used during training:38- learning_rate: 5e-0539- train_batch_size: 840- eval_batch_size: 841- seed: 4242- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments43- lr_scheduler_type: linear44- num_epochs: 1545- mixed_precision_training: Native AMP46 47### Training results48 49| Training Loss | Epoch | Step | Validation Loss |50|:-------------:|:-----:|:----:|:---------------:|51| 0.9758        | 1.0   | 41   | 0.6294          |52| 0.5964        | 2.0   | 82   | 0.4193          |53| 0.4172        | 3.0   | 123  | 0.3718          |54| 0.4899        | 4.0   | 164  | 0.3431          |55| 0.3984        | 5.0   | 205  | 0.3274          |56| 0.2469        | 6.0   | 246  | 0.3141          |57| 0.2722        | 7.0   | 287  | 0.3135          |58| 0.3021        | 8.0   | 328  | 0.3052          |59| 0.203         | 9.0   | 369  | 0.3035          |60| 0.1948        | 10.0  | 410  | 0.3049          |61| 0.1843        | 11.0  | 451  | 0.2965          |62| 0.1489        | 12.0  | 492  | 0.2889          |63| 0.1279        | 13.0  | 533  | 0.2921          |64| 0.1923        | 14.0  | 574  | 0.2919          |65| 0.1829        | 15.0  | 615  | 0.2914          |66 67 68### Framework versions69 70- Transformers 4.57.371- Pytorch 2.9.0+cu12672- Datasets 4.4.173- Tokenizers 0.22.174