CV30_finetuning – AI Model by Roshana | AlphaNeural AI

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CV30_finetuning

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CV30_finetuning

This model is a fine-tuned version of Roshana/CV11_finetuning1 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7956
Wer: 0.3677
Cer: 0.1436

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: 0.0003
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.1203	0.86	400	0.7747	0.4192	0.1656
0.2191	1.72	800	0.7546	0.4356	0.1771
0.213	2.59	1200	0.6965	0.4276	0.1709
0.1858	3.45	1600	0.7189	0.4156	0.1673
0.1597	4.31	2000	0.7462	0.4031	0.1606
0.1398	5.17	2400	0.7622	0.3944	0.1584
0.1245	6.03	2800	0.7527	0.3917	0.1553
0.1035	6.9	3200	0.7347	0.3819	0.1532
0.0918	7.76	3600	0.7825	0.3786	0.1497
0.0767	8.62	4000	0.7909	0.3724	0.1444
0.0722	9.48	4400	0.7956	0.3677	0.1436

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.7.1
Tokenizers 0.13.2