m-bert – AI Model by Rudra03 | AlphaNeural AI

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Rudra03/
m-bert

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token-classification

generated_from_trainer

google-bert/bert-base-multilingual-cased

autotrain_compatible

endpoints_compatible

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m-bert

This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3141
Precison: 0.8543
Recall: 0.8566
F1: 0.8554
Accuracy: 0.8594
Jaccard: 0.7848

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: 8
eval_batch_size: 8
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	Precison	Recall	F1	Accuracy	Jaccard
0.4088	1.0	1513	0.3141	0.8543	0.8566	0.8554	0.8594	0.7848
0.3328	2.0	3026	0.3161	0.8685	0.8530	0.8587	0.8656	0.8018
0.2521	3.0	4539	0.3444	0.8729	0.8700	0.8714	0.8758	0.8105

Framework versions

Transformers 4.41.1
Pytorch 2.1.2
Datasets 2.19.1
Tokenizers 0.19.1