--- license: apache-2.0 tags: - generated_from_trainer base_model: google/muril-base-cased widget: - text: >- मेयरले उपभोक्ता समितिसँग ३० प्रतिशत कमिसन लिएपछि विकासको काम गुणस्तरहीन, दबाब झेल्न नसकेर प्रशासकीय अधिकृतको भागाभाग। बाह्रबिसेका मेयरको मनोमानी- दोहोरीमा रमाइलो गरेको बिलसमेत नगरपालिकाबाटै भुक्तानी गर्न दबाब मेयरले उपभोक्ता समितिसँग ३० प्रतिशत कमिसन लिएपछि विकासको काम गुणस्तरहीन, दबाब झेल्न नसकेर प्रशासकीय अधिकृतको भागाभाग। model-index: - name: nepali_complaints_classification_muril3 results: [] --- # nepali_complaints_classification_muril3 This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.2575 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 50 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 2.3973 | 0.25 | 500 | 2.0247 | | 1.7073 | 0.5 | 1000 | 1.3814 | | 1.1586 | 0.75 | 1500 | 0.9054 | | 0.8099 | 1.0 | 2000 | 0.6431 | | 0.5456 | 1.25 | 2500 | 0.4845 | | 0.434 | 1.5 | 3000 | 0.4157 | | 0.3643 | 1.75 | 3500 | 0.3814 | | 0.3144 | 2.01 | 4000 | 0.3432 | | 0.2616 | 2.26 | 4500 | 0.3156 | | 0.2418 | 2.51 | 5000 | 0.2952 | | 0.2256 | 2.76 | 5500 | 0.2805 | | 0.2157 | 3.01 | 6000 | 0.2908 | | 0.1749 | 3.26 | 6500 | 0.2847 | | 0.1626 | 3.51 | 7000 | 0.2734 | | 0.1522 | 3.76 | 7500 | 0.2658 | | 0.1443 | 4.01 | 8000 | 0.2560 | | 0.1196 | 4.26 | 8500 | 0.2580 | | 0.1138 | 4.51 | 9000 | 0.2618 | | 0.1119 | 4.76 | 9500 | 0.2575 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.1.0+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2