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nepali_gov_complaints_classification2
nadika/nepali_gov_complaints_classification2
nepali_gov_complaints_classification2 is a text classification model from nadika. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 10, 2024
- Updated
- Mar 10, 2024
- SHA
- 506f40fe
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
nepali_gov_complaints_classification2
This model is a fine-tuned version of Rajan/NepaliBERT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2107
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: 1000
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.5513 | 1.0 | 2244 | 0.4012 |
| 0.2279 | 2.0 | 4488 | 0.2421 |
| 0.0729 | 3.0 | 6732 | 0.2050 |
| 0.197 | 4.0 | 8976 | 0.2118 |
| 0.029 | 5.0 | 11220 | 0.2107 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Mar 10, 2024
- Updated
- Mar 10, 2024