metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: indic-bert-finetuned-non-code-mixed-DS
results: []
indic-bert-finetuned-non-code-mixed-DS
This model is a fine-tuned version of ai4bharat/indic-bert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9997
- Accuracy: 0.5620
- Precision: 0.5591
- Recall: 0.5203
- F1: 0.5078
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: 1e-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 43
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.0673 | 3.99 | 926 | 1.0361 | 0.4142 | 0.4092 | 0.3851 | 0.2750 |
| 1.0144 | 7.98 | 1852 | 1.0147 | 0.5146 | 0.5851 | 0.4714 | 0.4184 |
| 0.9882 | 11.97 | 2778 | 1.0045 | 0.5599 | 0.5728 | 0.5191 | 0.5047 |
| 0.9699 | 15.97 | 3704 | 1.0004 | 0.5642 | 0.5620 | 0.5264 | 0.5193 |
| 0.9591 | 19.96 | 4630 | 0.9997 | 0.5620 | 0.5591 | 0.5203 | 0.5078 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1