transformers tensorboard safetensors albert fill-mask generated_from_trainer base_model:neuropark/sahajBERT license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: neuropark/sahajBERT
tags:
- generated_from_trainer
model-index:
- name: shahajbert_nwp_finetuning_def_v1
  results: []
---

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# shahajbert_nwp_finetuning_def_v1

This model is a fine-tuned version of [neuropark/sahajBERT](https://huggingface.co/neuropark/sahajBERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3686

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.4643        | 1.0   | 1294  | 3.4986          |
| 3.3773        | 2.0   | 2588  | 3.4239          |
| 3.3263        | 3.0   | 3882  | 3.4514          |
| 3.253         | 4.0   | 5176  | 3.4217          |
| 3.1767        | 5.0   | 6470  | 3.3953          |
| 3.1382        | 6.0   | 7764  | 3.3723          |
| 3.0959        | 7.0   | 9058  | 3.3533          |
| 3.0717        | 8.0   | 10352 | 3.3841          |
| 3.0472        | 9.0   | 11646 | 3.3747          |
| 3.003         | 10.0  | 12940 | 3.4074          |
| 2.9259        | 11.0  | 14234 | 3.3752          |
| 2.9641        | 12.0  | 15528 | 3.4120          |
| 2.9016        | 13.0  | 16822 | 3.3769          |
| 2.9102        | 14.0  | 18116 | 3.4494          |
| 2.8359        | 15.0  | 19410 | 3.3717          |
| 2.8327        | 16.0  | 20704 | 3.3801          |
| 2.7914        | 17.0  | 21998 | 3.4244          |
| 2.776         | 18.0  | 23292 | 3.3533          |
| 2.7258        | 19.0  | 24586 | 3.3669          |
| 2.7304        | 20.0  | 25880 | 3.3113          |
| 2.6619        | 21.0  | 27174 | 3.3531          |
| 2.6721        | 22.0  | 28468 | 3.3728          |
| 2.6387        | 23.0  | 29762 | 3.4085          |
| 2.6302        | 24.0  | 31056 | 3.3909          |
| 2.5952        | 25.0  | 32350 | 3.3288          |
| 2.5854        | 26.0  | 33644 | 3.3465          |
| 2.5597        | 27.0  | 34938 | 3.3854          |
| 2.5667        | 28.0  | 36232 | 3.3977          |
| 2.5189        | 29.0  | 37526 | 3.4447          |
| 2.5253        | 30.0  | 38820 | 3.4329          |
| 2.5013        | 31.0  | 40114 | 3.3689          |
| 2.4165        | 32.0  | 41408 | 3.4354          |
| 2.4414        | 33.0  | 42702 | 3.4247          |
| 2.4435        | 34.0  | 43996 | 3.4555          |
| 2.3846        | 35.0  | 45290 | 3.3626          |
| 2.3611        | 36.0  | 46584 | 3.4496          |
| 2.3753        | 37.0  | 47878 | 3.4788          |
| 2.3526        | 38.0  | 49172 | 3.4418          |
| 2.3543        | 39.0  | 50466 | 3.4803          |
| 2.3279        | 40.0  | 51760 | 3.4240          |
| 2.3388        | 41.0  | 53054 | 3.4378          |
| 2.3182        | 42.0  | 54348 | 3.4351          |
| 2.3118        | 43.0  | 55642 | 3.4245          |
| 2.3033        | 44.0  | 56936 | 3.4708          |
| 2.2757        | 45.0  | 58230 | 3.4062          |
| 2.2733        | 46.0  | 59524 | 3.5356          |
| 2.2746        | 47.0  | 60818 | 3.4078          |
| 2.2683        | 48.0  | 62112 | 3.4636          |
| 2.2498        | 49.0  | 63406 | 3.4752          |
| 2.2418        | 50.0  | 64700 | 3.4336          |


### Framework versions

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