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---
license: mit
base_model: sagorsarker/bangla-bert-base
tags:
- generated_from_trainer
model-index:
- name: sagorbert_nwp_finetuning_test4
results: []
---
<!-- 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. -->
# sagorbert_nwp_finetuning_test4
This model is a fine-tuned version of [sagorsarker/bangla-bert-base](https://huggingface.co/sagorsarker/bangla-bert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8149
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 4.7767 | 1.0 | 544 | 4.2674 |
| 4.1049 | 2.0 | 1088 | 3.8654 |
| 3.7943 | 3.0 | 1632 | 3.6822 |
| 3.5949 | 4.0 | 2176 | 3.6292 |
| 3.4489 | 5.0 | 2720 | 3.4425 |
| 3.2806 | 6.0 | 3264 | 3.4347 |
| 3.1905 | 7.0 | 3808 | 3.3484 |
| 3.1216 | 8.0 | 4352 | 3.2960 |
| 2.9871 | 9.0 | 4896 | 3.2927 |
| 2.9642 | 10.0 | 5440 | 3.2930 |
| 2.8607 | 11.0 | 5984 | 3.2112 |
| 2.7493 | 12.0 | 6528 | 3.1386 |
| 2.7057 | 13.0 | 7072 | 3.1607 |
| 2.6244 | 14.0 | 7616 | 3.1132 |
| 2.6006 | 15.0 | 8160 | 3.0764 |
| 2.521 | 16.0 | 8704 | 3.1419 |
| 2.4752 | 17.0 | 9248 | 3.0641 |
| 2.4493 | 18.0 | 9792 | 2.9287 |
| 2.4133 | 19.0 | 10336 | 3.0460 |
| 2.3448 | 20.0 | 10880 | 3.0339 |
| 2.3252 | 21.0 | 11424 | 2.9302 |
| 2.2843 | 22.0 | 11968 | 2.9520 |
| 2.2266 | 23.0 | 12512 | 2.9751 |
| 2.1527 | 24.0 | 13056 | 2.8732 |
| 2.1661 | 25.0 | 13600 | 2.9094 |
| 2.1001 | 26.0 | 14144 | 2.8885 |
| 2.0863 | 27.0 | 14688 | 2.9079 |
| 2.079 | 28.0 | 15232 | 2.8848 |
| 2.0468 | 29.0 | 15776 | 2.7729 |
| 2.0064 | 30.0 | 16320 | 2.9156 |
| 2.0025 | 31.0 | 16864 | 2.8439 |
| 1.9941 | 32.0 | 17408 | 2.8801 |
| 1.9787 | 33.0 | 17952 | 2.8806 |
| 1.9317 | 34.0 | 18496 | 2.8564 |
| 1.8991 | 35.0 | 19040 | 2.8786 |
| 1.8881 | 36.0 | 19584 | 2.9111 |
| 1.8497 | 37.0 | 20128 | 2.8445 |
| 1.846 | 38.0 | 20672 | 2.7834 |
| 1.8254 | 39.0 | 21216 | 2.8369 |
| 1.8306 | 40.0 | 21760 | 2.8321 |
| 1.8062 | 41.0 | 22304 | 2.8028 |
| 1.7845 | 42.0 | 22848 | 2.8520 |
| 1.7953 | 43.0 | 23392 | 2.7625 |
| 1.7628 | 44.0 | 23936 | 2.8242 |
| 1.7593 | 45.0 | 24480 | 2.8058 |
| 1.7384 | 46.0 | 25024 | 2.8107 |
| 1.7426 | 47.0 | 25568 | 2.8554 |
| 1.7366 | 48.0 | 26112 | 2.7281 |
| 1.7453 | 49.0 | 26656 | 2.7387 |
| 1.7375 | 50.0 | 27200 | 2.7897 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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