README.md

metadata

tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: transliterate
    results: []

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