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# transliterate

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0324
- Precision: 0.9912
- Recall: 0.9912
- F1: 0.9912
- Accuracy: 0.9912

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 64   | 0.1049          | 0.9654    | 0.9654 | 0.9654 | 0.9654   |
| No log        | 2.0   | 128  | 0.0665          | 0.9796    | 0.9796 | 0.9796 | 0.9796   |
| No log        | 3.0   | 192  | 0.0513          | 0.9848    | 0.9848 | 0.9848 | 0.9848   |
| No log        | 4.0   | 256  | 0.0434          | 0.9871    | 0.9871 | 0.9871 | 0.9871   |
| No log        | 5.0   | 320  | 0.0390          | 0.9888    | 0.9888 | 0.9888 | 0.9888   |
| No log        | 6.0   | 384  | 0.0364          | 0.9897    | 0.9897 | 0.9897 | 0.9897   |
| No log        | 7.0   | 448  | 0.0345          | 0.9905    | 0.9905 | 0.9905 | 0.9905   |
| No log        | 8.0   | 512  | 0.0334          | 0.9908    | 0.9908 | 0.9908 | 0.9908   |
| No log        | 9.0   | 576  | 0.0334          | 0.9908    | 0.9908 | 0.9908 | 0.9908   |
| No log        | 10.0  | 640  | 0.0324          | 0.9912    | 0.9912 | 0.9912 | 0.9912   |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.13.0+cu117
- Datasets 2.11.0
- Tokenizers 0.11.6

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "transliterate", "results": []}]}
transformers pytorch tensorboard bert token-classification generated_from_trainer doi:10.57967/hf/0641 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #doi-10.57967/hf/0641 #autotrain_compatible #endpoints_compatible #region-us 

transliterate
=============


This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0324
* Precision: 0.9912
* Recall: 0.9912
* F1: 0.9912
* Accuracy: 0.9912


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: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.0+cu117
* Datasets 2.11.0
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.0+cu117
* Datasets 2.11.0
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #doi-10.57967/hf/0641 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.0+cu117
* Datasets 2.11.0
* Tokenizers 0.11.6