callmesan/indic-bert-hate-mr

1---2library_name: transformers3license: mit4base_model: ai4bharat/indic-bert5tags:6- generated_from_trainer7metrics:8- accuracy9- precision10- recall11- f112model-index:13- name: indic-bert-hate-mr14  results: []15---16 17<!-- This model card has been generated automatically according to the information the Trainer had access to. You18should probably proofread and complete it, then remove this comment. -->19 20# indic-bert-hate-mr21 22This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) on the None dataset.23It achieves the following results on the evaluation set:24- Loss: 0.240825- Accuracy: 0.922626- Precision: 0.927027- Recall: 0.922528- F1: 0.922429 30## Model description31 32More information needed33 34## Intended uses & limitations35 36More information needed37 38## Training and evaluation data39 40More information needed41 42## Training procedure43 44### Training hyperparameters45 46The following hyperparameters were used during training:47- learning_rate: 5e-0548- train_batch_size: 1649- eval_batch_size: 12850- seed: 4251- gradient_accumulation_steps: 252- total_train_batch_size: 3253- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0854- lr_scheduler_type: linear55- num_epochs: 1056 57### Training results58 59| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |60|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|61| 0.6637        | 1.0   | 61   | 0.6441          | 0.6530   | 0.6780    | 0.6526 | 0.6400 |62| 0.678         | 2.0   | 122  | 0.6538          | 0.6386   | 0.6408    | 0.6387 | 0.6372 |63| 0.6422        | 3.0   | 183  | 0.6597          | 0.6410   | 0.6607    | 0.6405 | 0.6292 |64| 0.6281        | 4.0   | 244  | 0.6202          | 0.6578   | 0.6591    | 0.6579 | 0.6573 |65| 0.5374        | 5.0   | 305  | 0.6306          | 0.6723   | 0.6746    | 0.6721 | 0.6711 |66| 0.4418        | 6.0   | 366  | 0.7122          | 0.6795   | 0.6991    | 0.6799 | 0.6717 |67| 0.3981        | 7.0   | 427  | 0.7183          | 0.6602   | 0.6603    | 0.6602 | 0.6602 |68| 0.3054        | 8.0   | 488  | 0.8008          | 0.6867   | 0.6889    | 0.6869 | 0.6859 |69| 0.2445        | 9.0   | 549  | 0.9741          | 0.6578   | 0.6587    | 0.6577 | 0.6573 |70| 0.1882        | 10.0  | 610  | 0.9924          | 0.6723   | 0.6723    | 0.6723 | 0.6723 |71 72 73### Framework versions74 75- Transformers 4.45.176- Pytorch 2.4.077- Datasets 3.0.178- Tokenizers 0.20.079