File size: 1,909 Bytes
d96c296
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
---
license: apache-2.0
base_model: google/muril-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: urdu-muril-ner
  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. -->

# urdu-muril-ner

This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co./google/muril-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1489
- Precision: 0.7802
- Recall: 0.8229
- F1: 0.8009
- Accuracy: 0.9570

## 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3946        | 1.0   | 2272  | 0.3188          | 0.7387    | 0.6442 | 0.6882 | 0.9350   |
| 0.2026        | 2.0   | 4544  | 0.1960          | 0.7728    | 0.7797 | 0.7762 | 0.9535   |
| 0.141         | 3.0   | 6816  | 0.1554          | 0.7735    | 0.8139 | 0.7932 | 0.9557   |
| 0.1038        | 4.0   | 9088  | 0.1474          | 0.7836    | 0.8163 | 0.7996 | 0.9568   |
| 0.0889        | 5.0   | 11360 | 0.1489          | 0.7802    | 0.8229 | 0.8009 | 0.9570   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1