WAXAL-mas-lug-sog-w2v-bert-2.0 – AI Model by dhasmana | AlphaNeural AI

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dhasmana/
WAXAL-mas-lug-sog-w2v-bert-2.0

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automatic-speech-recognition

generated_from_trainer

facebook/w2v-bert-2.0

endpoints_compatible

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WAXAL-mas-lug-sog-w2v-bert-2.0

This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4913
Cer: 0.0871

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: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
8.5286	1.5088	300	0.6984	0.1722
1.5726	3.0151	600	0.5030	0.1168
0.8499	4.5239	900	0.4128	0.0979
0.5808	6.0302	1200	0.3862	0.0906
0.3597	7.5390	1500	0.4201	0.0886
0.2199	9.0453	1800	0.4574	0.0869
0.2199	10.0	1990	0.4913	0.0871

Framework versions

Transformers 5.13.0
Pytorch 2.13.0+cu130
Datasets 5.0.0
Tokenizers 0.22.2