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---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: sindhi-bert-ner
results: []
datasets:
- mirfan899/sindhi-ner
language:
- sd
---
<!-- 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. -->
# sindhi-bert-ner
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1513
- Precision: 0.7080
- Recall: 0.6443
- F1: 0.6746
- Accuracy: 0.9704
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1578 | 1.0 | 2252 | 0.1457 | 0.7162 | 0.5285 | 0.6082 | 0.9640 |
| 0.1162 | 2.0 | 4504 | 0.1280 | 0.7296 | 0.5718 | 0.6411 | 0.9676 |
| 0.097 | 3.0 | 6756 | 0.1248 | 0.7040 | 0.6065 | 0.6516 | 0.9678 |
| 0.0803 | 4.0 | 9008 | 0.1265 | 0.7442 | 0.6078 | 0.6691 | 0.9707 |
| 0.0719 | 5.0 | 11260 | 0.1274 | 0.7459 | 0.6181 | 0.6760 | 0.9707 |
| 0.056 | 6.0 | 13512 | 0.1333 | 0.7083 | 0.6383 | 0.6715 | 0.9704 |
| 0.0507 | 7.0 | 15764 | 0.1339 | 0.7157 | 0.6378 | 0.6745 | 0.9709 |
| 0.0441 | 8.0 | 18016 | 0.1445 | 0.7308 | 0.6284 | 0.6758 | 0.9710 |
| 0.0377 | 9.0 | 20268 | 0.1487 | 0.7253 | 0.6307 | 0.6747 | 0.9705 |
| 0.0344 | 10.0 | 22520 | 0.1513 | 0.7080 | 0.6443 | 0.6746 | 0.9704 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.13.3 |