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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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base_model: google/muril-base-cased |
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model-index: |
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- name: nepali_complaints_classification_muril2 |
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results: [] |
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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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# nepali_complaints_classification_muril2 |
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This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6391 |
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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: 0.0003 |
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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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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 2.641 | 0.22 | 500 | 2.6403 | |
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| 2.6415 | 0.45 | 1000 | 2.6393 | |
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| 2.6399 | 0.67 | 1500 | 2.6393 | |
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| 2.64 | 0.89 | 2000 | 2.6395 | |
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| 2.6398 | 1.11 | 2500 | 2.6395 | |
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| 2.64 | 1.34 | 3000 | 2.6392 | |
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| 2.64 | 1.56 | 3500 | 2.6392 | |
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| 2.6387 | 1.78 | 4000 | 2.6402 | |
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| 2.64 | 2.01 | 4500 | 2.6391 | |
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| 2.6396 | 2.23 | 5000 | 2.6392 | |
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| 2.6394 | 2.45 | 5500 | 2.6391 | |
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| 2.64 | 2.67 | 6000 | 2.6392 | |
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| 2.6398 | 2.9 | 6500 | 2.6391 | |
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| 2.6395 | 3.12 | 7000 | 2.6391 | |
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| 2.6392 | 3.34 | 7500 | 2.6391 | |
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| 2.6384 | 3.57 | 8000 | 2.6394 | |
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| 2.6392 | 3.79 | 8500 | 2.6391 | |
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| 2.6392 | 4.01 | 9000 | 2.6391 | |
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| 2.639 | 4.23 | 9500 | 2.6391 | |
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| 2.6391 | 4.46 | 10000 | 2.6391 | |
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| 2.6391 | 4.68 | 10500 | 2.6391 | |
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| 2.6391 | 4.9 | 11000 | 2.6391 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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