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---
base_model: mHossain/bengali_pos_v1_400000
tags:
- generated_from_trainer
datasets:
- pos_tag_100k
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bengali_pos_v1_300000
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: pos_tag_100k
type: pos_tag_100k
config: conll2003
split: validation
args: conll2003
metrics:
- name: Precision
type: precision
value: 0.7758382692500753
- name: Recall
type: recall
value: 0.7796834604956177
- name: F1
type: f1
value: 0.7777561122887353
- name: Accuracy
type: accuracy
value: 0.8338714666872897
---
<!-- 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. -->
# bengali_pos_v1_300000
This model is a fine-tuned version of [mHossain/bengali_pos_v1_400000](https://huggingface.co/mHossain/bengali_pos_v1_400000) on the pos_tag_100k dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5865
- Precision: 0.7758
- Recall: 0.7797
- F1: 0.7778
- Accuracy: 0.8339
## 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.587 | 1.0 | 22500 | 0.5821 | 0.7614 | 0.7643 | 0.7628 | 0.8232 |
| 0.4808 | 2.0 | 45000 | 0.5726 | 0.7733 | 0.7762 | 0.7747 | 0.8316 |
| 0.3909 | 3.0 | 67500 | 0.5865 | 0.7758 | 0.7797 | 0.7778 | 0.8339 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
|