mamiksik/CodeBertaCLM

1---2tags:3- generated_from_trainer4metrics:5- accuracy6- f17model-index:8- name: CodeBertaCLM9  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# CodeBertaCLM16 17This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on the None dataset.18It achieves the following results on the evaluation set:19- Loss: 2.583120- Accuracy: 0.014421- F1: 0.014422- Bleu4: 0.042123 24## Model description25 26More information needed27 28## Intended uses & limitations29 30More information needed31 32## Training and evaluation data33 34More information needed35 36## Training procedure37 38### Training hyperparameters39 40The following hyperparameters were used during training:41- learning_rate: 2e-0542- train_batch_size: 3243- eval_batch_size: 3244- seed: 4245- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0846- lr_scheduler_type: linear47- num_epochs: 20048 49### Training results50 51| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Bleu4  |52|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|53| 3.6734        | 1.0   | 1673  | 3.6884          | 0.0159   | 0.0159 | 0.0131 |54| 2.8139        | 2.0   | 3346  | 3.2517          | 0.0164   | 0.0164 | 0.0192 |55| 2.4176        | 3.0   | 5019  | 3.0747          | 0.0178   | 0.0178 | 0.0332 |56| 2.2785        | 4.0   | 6692  | 2.9695          | 0.0174   | 0.0174 | 0.0347 |57| 2.1557        | 5.0   | 8365  | 2.8886          | 0.0171   | 0.0171 | 0.0377 |58| 2.0357        | 6.0   | 10038 | 2.8313          | 0.0158   | 0.0158 | 0.0394 |59| 1.9615        | 7.0   | 11711 | 2.7865          | 0.0158   | 0.0158 | 0.0393 |60| 1.8982        | 8.0   | 13384 | 2.7498          | 0.0147   | 0.0147 | 0.0399 |61| 1.8233        | 9.0   | 15057 | 2.7195          | 0.0149   | 0.0149 | 0.0430 |62| 1.7866        | 10.0  | 16730 | 2.6925          | 0.0157   | 0.0157 | 0.0485 |63| 1.7237        | 11.0  | 18403 | 2.6745          | 0.0146   | 0.0146 | 0.0419 |64| 1.6757        | 12.0  | 20076 | 2.6616          | 0.0146   | 0.0146 | 0.0403 |65| 1.6452        | 13.0  | 21749 | 2.6377          | 0.0147   | 0.0147 | 0.0403 |66| 1.6036        | 14.0  | 23422 | 2.6216          | 0.0145   | 0.0145 | 0.0397 |67| 1.5818        | 15.0  | 25095 | 2.6169          | 0.0150   | 0.0150 | 0.0413 |68| 1.5389        | 16.0  | 26768 | 2.6047          | 0.0146   | 0.0146 | 0.0420 |69| 1.5131        | 17.0  | 28441 | 2.5940          | 0.0153   | 0.0153 | 0.0433 |70| 1.4822        | 18.0  | 30114 | 2.5899          | 0.0145   | 0.0145 | 0.0404 |71| 1.4461        | 19.0  | 31787 | 2.5812          | 0.0150   | 0.0150 | 0.0423 |72| 1.4149        | 20.0  | 33460 | 2.5841          | 0.0148   | 0.0148 | 0.0418 |73| 1.3933        | 21.0  | 35133 | 2.5783          | 0.0139   | 0.0139 | 0.0386 |74| 1.3752        | 22.0  | 36806 | 2.5730          | 0.0151   | 0.0151 | 0.0444 |75| 1.3412        | 23.0  | 38479 | 2.5709          | 0.0149   | 0.0149 | 0.0419 |76| 1.3307        | 24.0  | 40152 | 2.5699          | 0.0143   | 0.0143 | 0.0424 |77| 1.2909        | 25.0  | 41825 | 2.5648          | 0.0144   | 0.0144 | 0.0416 |78| 1.2679        | 26.0  | 43498 | 2.5615          | 0.0145   | 0.0145 | 0.0420 |79| 1.2603        | 27.0  | 45171 | 2.5626          | 0.0148   | 0.0148 | 0.0433 |80| 1.2203        | 28.0  | 46844 | 2.5670          | 0.0148   | 0.0148 | 0.0410 |81| 1.2134        | 29.0  | 48517 | 2.5536          | 0.0147   | 0.0147 | 0.0422 |82| 1.1907        | 30.0  | 50190 | 2.5701          | 0.0139   | 0.0139 | 0.0404 |83| 1.1702        | 31.0  | 51863 | 2.5722          | 0.0143   | 0.0143 | 0.0424 |84| 1.1555        | 32.0  | 53536 | 2.5679          | 0.0144   | 0.0144 | 0.0434 |85| 1.1371        | 33.0  | 55209 | 2.5694          | 0.0146   | 0.0146 | 0.0431 |86| 1.1189        | 34.0  | 56882 | 2.5692          | 0.0141   | 0.0141 | 0.0422 |87| 1.0989        | 35.0  | 58555 | 2.5831          | 0.0144   | 0.0144 | 0.0421 |88 89 90### Framework versions91 92- Transformers 4.25.193- Pytorch 1.13.0+cu11794- Datasets 2.7.195- Tokenizers 0.13.296