w2v-bert-2.0-Chinese-colab-CV16.0-aishell-ark-gs-vtb-new_tokenizer – AI Model by urarik | AlphaNeural AI

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urarik/
w2v-bert-2.0-Chinese-colab-CV16.0-aishell-ark-gs-vtb-new_tokenizer

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automatic-speech-recognition

generated_from_trainer

facebook/w2v-bert-2.0

endpoints_compatible

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w2v-bert-2.0-Chinese-colab-CV16.0-aishell-ark-gs-vtb-new_tokenizer

This model is a fine-tuned version of facebook/w2v-bert-2.0 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.2200
Wer: 1.7271

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: 4
seed: 42
gradient_accumulation_steps: 64
total_train_batch_size: 256
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.059	0.9976	156	1.4359	1.7492
2.9898	1.9912	312	1.3586	1.8124
2.17	2.9848	468	1.2909	1.7153
1.9683	3.9784	624	1.2440	1.7769
1.6888	4.9720	780	1.2200	1.7271

Framework versions

Transformers 4.49.0
Pytorch 2.5.1+cu121
Datasets 2.17.1
Tokenizers 0.21.0