Bert-Multilingual-Balanced-trimmed-10epoch – AI Model by Harsha9044 | AlphaNeural AI

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Harsha9044/
Bert-Multilingual-Balanced-trimmed-10epoch

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text-classification

generated_from_trainer

google-bert/bert-base-multilingual-cased

autotrain_compatible

endpoints_compatible

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Bert-Multilingual-Balanced-trimmed-10epoch

This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.5212
Accuracy: 0.48

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: 10
eval_batch_size: 10
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	4	1.1339	0.32
No log	2.0	8	1.0996	0.48
No log	3.0	12	1.1665	0.36
No log	4.0	16	1.1651	0.44
No log	5.0	20	1.1689	0.4
No log	6.0	24	1.2189	0.32
No log	7.0	28	1.1908	0.44
No log	8.0	32	1.1355	0.52
No log	9.0	36	1.2280	0.4
No log	10.0	40	1.3308	0.4
No log	11.0	44	1.3048	0.48
No log	12.0	48	1.3897	0.44
No log	13.0	52	1.3561	0.44
No log	14.0	56	1.3551	0.52
No log	15.0	60	1.5895	0.4
No log	16.0	64	1.7362	0.36
No log	17.0	68	1.6214	0.4
No log	18.0	72	1.5556	0.4
No log	19.0	76	1.5258	0.48
No log	20.0	80	1.5212	0.48

Framework versions

Transformers 4.35.0.dev0
Pytorch 1.13.1
Datasets 2.14.5
Tokenizers 0.14.1