transformers tensorboard safetensors bert fill-mask generated_from_trainer base_model:sagorsarker/bangla-bert-base license:mit autotrain_compatible endpoints_compatible region:us
---
license: mit
base_model: sagorsarker/bangla-bert-base
tags:
- generated_from_trainer
model-index:
- name: sagorbert_nwp_finetuning_def_v3
  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_def_v3

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: 2.7146

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 4.1717        | 1.0   | 1551  | 3.9996          |
| 3.7173        | 2.0   | 3102  | 3.6406          |
| 3.4565        | 3.0   | 4653  | 3.4235          |
| 3.2657        | 4.0   | 6204  | 3.2330          |
| 3.1522        | 5.0   | 7755  | 3.2134          |
| 3.0686        | 6.0   | 9306  | 3.1522          |
| 2.9315        | 7.0   | 10857 | 3.0937          |
| 2.8902        | 8.0   | 12408 | 3.0556          |
| 2.7995        | 9.0   | 13959 | 3.0475          |
| 2.7451        | 10.0  | 15510 | 2.9813          |
| 2.7015        | 11.0  | 17061 | 2.9560          |
| 2.6528        | 12.0  | 18612 | 2.9613          |
| 2.5797        | 13.0  | 20163 | 2.9195          |
| 2.5343        | 14.0  | 21714 | 2.8609          |
| 2.4927        | 15.0  | 23265 | 2.8933          |
| 2.4433        | 16.0  | 24816 | 2.8718          |
| 2.3995        | 17.0  | 26367 | 2.8405          |
| 2.3875        | 18.0  | 27918 | 2.8703          |
| 2.3171        | 19.0  | 29469 | 2.8371          |
| 2.319         | 20.0  | 31020 | 2.8027          |
| 2.2824        | 21.0  | 32571 | 2.7959          |
| 2.2633        | 22.0  | 34122 | 2.8165          |
| 2.2149        | 23.0  | 35673 | 2.7747          |
| 2.1812        | 24.0  | 37224 | 2.7879          |
| 2.1677        | 25.0  | 38775 | 2.7723          |
| 2.1521        | 26.0  | 40326 | 2.7887          |
| 2.14          | 27.0  | 41877 | 2.7839          |
| 2.059         | 28.0  | 43428 | 2.8150          |
| 2.0881        | 29.0  | 44979 | 2.7617          |
| 2.0583        | 30.0  | 46530 | 2.7491          |
| 2.0574        | 31.0  | 48081 | 2.7303          |
| 2.0416        | 32.0  | 49632 | 2.7490          |
| 1.9837        | 33.0  | 51183 | 2.7419          |
| 1.9747        | 34.0  | 52734 | 2.7409          |
| 1.9486        | 35.0  | 54285 | 2.7757          |
| 1.941         | 36.0  | 55836 | 2.7546          |
| 1.9549        | 37.0  | 57387 | 2.7046          |
| 1.9346        | 38.0  | 58938 | 2.7700          |
| 1.8979        | 39.0  | 60489 | 2.7033          |
| 1.9104        | 40.0  | 62040 | 2.7383          |
| 1.8989        | 41.0  | 63591 | 2.6837          |
| 1.8691        | 42.0  | 65142 | 2.7084          |
| 1.8492        | 43.0  | 66693 | 2.7000          |
| 1.8271        | 44.0  | 68244 | 2.6792          |
| 1.8723        | 45.0  | 69795 | 2.7325          |
| 1.8208        | 46.0  | 71346 | 2.6998          |
| 1.8218        | 47.0  | 72897 | 2.7490          |
| 1.8305        | 48.0  | 74448 | 2.7394          |
| 1.8067        | 49.0  | 75999 | 2.6545          |
| 1.7974        | 50.0  | 77550 | 2.6925          |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
