metadata
library_name: transformers
license: mit
base_model: ai4bharat/indic-bert
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: indic-bert-roman-urdu-fine-grained
results: []
indic-bert-roman-urdu-fine-grained
This model is a fine-tuned version of ai4bharat/indic-bert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8501
- Accuracy: 0.7678
- Precision: 0.6945
- Recall: 0.6537
- F1: 0.6720
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.1237 | 1.0 | 113 | 1.0947 | 0.5342 | 0.1068 | 0.2 | 0.1393 |
| 0.9606 | 2.0 | 226 | 0.8776 | 0.6689 | 0.4456 | 0.3188 | 0.2779 |
| 0.7784 | 3.0 | 339 | 0.6443 | 0.7896 | 0.7017 | 0.6830 | 0.6899 |
| 0.5626 | 4.0 | 452 | 0.5167 | 0.8302 | 0.7561 | 0.7371 | 0.7422 |
| 0.5613 | 5.0 | 565 | 0.4285 | 0.8634 | 0.7931 | 0.7849 | 0.7850 |
| 0.4232 | 6.0 | 678 | 0.3543 | 0.8867 | 0.8295 | 0.8072 | 0.8155 |
| 0.3376 | 7.0 | 791 | 0.2546 | 0.9293 | 0.8850 | 0.8757 | 0.8802 |
| 0.2759 | 8.0 | 904 | 0.2079 | 0.9469 | 0.9085 | 0.9132 | 0.9103 |
| 0.2029 | 9.0 | 1017 | 0.1564 | 0.9606 | 0.9370 | 0.9276 | 0.9322 |
| 0.137 | 10.0 | 1130 | 0.1364 | 0.9685 | 0.9558 | 0.9399 | 0.9477 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0