|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: ai4bharat/indic-bert |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
- precision |
|
|
- recall |
|
|
- f1 |
|
|
model-index: |
|
|
- name: indic-bert-profanity-mr |
|
|
results: [] |
|
|
--- |
|
|
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
|
|
# indic-bert-profanity-mr |
|
|
|
|
|
This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.3187 |
|
|
- Accuracy: 0.9035 |
|
|
- Precision: 0.4517 |
|
|
- Recall: 0.5 |
|
|
- F1: 0.4746 |
|
|
|
|
|
## 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 | |
|
|
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
|
| 0.3272 | 0.9836 | 30 | 0.3721 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
|
|
| 0.3332 | 2.0 | 61 | 0.3677 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
|
|
| 0.3293 | 2.9836 | 91 | 0.3768 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
|
|
| 0.3275 | 4.0 | 122 | 0.3612 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
|
|
| 0.2919 | 4.9836 | 152 | 0.3752 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
|
|
| 0.291 | 6.0 | 183 | 0.3618 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
|
|
| 0.281 | 6.9836 | 213 | 0.3793 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
|
|
| 0.2399 | 8.0 | 244 | 0.3854 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
|
|
| 0.1822 | 8.9836 | 274 | 0.4216 | 0.8819 | 0.4410 | 0.5 | 0.4686 | |
|
|
| 0.1354 | 9.8361 | 300 | 0.4200 | 0.8819 | 0.6938 | 0.5265 | 0.5229 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.45.1 |
|
|
- Pytorch 2.4.0 |
|
|
- Datasets 3.0.1 |
|
|
- Tokenizers 0.20.0 |
|
|
|
