metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: model_indicbert_small
results: []
model_indicbert_small
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: 0.1079
- Precision: 0.9141
- Recall: 0.9076
- F1: 0.9109
- Accuracy: 0.9652
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: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1584 | 1.0 | 8806 | 0.1524 | 0.8780 | 0.8698 | 0.8739 | 0.9499 |
| 0.1149 | 2.0 | 17612 | 0.1217 | 0.9032 | 0.8961 | 0.8996 | 0.9606 |
| 0.0925 | 3.0 | 26418 | 0.1079 | 0.9141 | 0.9076 | 0.9109 | 0.9652 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3