pseudolabeling-step2-F01-Pass-2 – AI Model by monideep2255 | AlphaNeural AI

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pseudolabeling-step2-F01-Pass-2

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pseudolabeling-step2-F01-Pass-2

This model is a fine-tuned version of monideep2255/XLRS-torgo on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.2704
Wer: 1.1942

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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.9509	2.94	400	1.1949	1.2734
0.5686	5.88	800	1.0452	1.2266
0.4179	8.82	1200	1.1876	1.2032
0.3137	11.76	1600	1.2691	1.2572
0.2329	14.7	2000	1.2944	1.2104
0.1851	17.64	2400	1.4389	1.2626
0.1427	20.59	2800	1.3325	1.2608
0.1101	23.53	3200	1.4132	1.2176
0.0805	26.47	3600	1.3443	1.2482
0.0645	29.41	4000	1.2704	1.1942

Framework versions

Transformers 4.23.1
Pytorch 1.12.1+cu113
Datasets 1.18.3
Tokenizers 0.13.2