indic-bert-abusive-comments-ta – AI Model by callmesan | AlphaNeural AI

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callmesan/
indic-bert-abusive-comments-ta

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text-classification

generated_from_trainer

ai4bharat/indic-bert

autotrain_compatible

endpoints_compatible

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indic-bert-abusive-comments-ta

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: 1.1108
Accuracy: 0.6896
Precision: 0.2983
Recall: 0.2872
F1: 0.2740

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
1.1508	1.0	93	1.2143	0.6216	0.1373	0.1440	0.1253
1.1999	2.0	186	1.1389	0.6337	0.1632	0.1656	0.1545
1.0445	3.0	279	1.0623	0.6815	0.2057	0.2219	0.2109
0.882	4.0	372	1.0181	0.6996	0.3264	0.3092	0.2976
0.7892	5.0	465	1.0408	0.7036	0.3327	0.3097	0.3011
0.7381	6.0	558	1.1007	0.7103	0.3317	0.3060	0.3057
0.6175	7.0	651	1.2323	0.7070	0.3241	0.3014	0.3037
0.49	8.0	744	1.2686	0.6956	0.4590	0.3093	0.3164
0.4576	9.0	837	1.3347	0.6761	0.3285	0.3200	0.3199
0.3436	10.0	930	1.3501	0.6673	0.3363	0.3167	0.3204

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0