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w2v2-BERT_kabir – AI Model by Kabir259 | AlphaNeural AI
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Kabir259
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w2v2-BERT_kabir
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transformers
tensorboard
safetensors
wav2vec2-bert
automatic-speech-recognition
generated_from_trainer
facebook/w2v-bert-2.0
finetune
mit
endpoints_compatible
us
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w2v2-BERT_kabir
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: inf
Wer: 0.2462
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: 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: cosine
lr_scheduler_warmup_steps: 200
training_steps: 1000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0824
20.8333
500
inf
0.2310
0.062
41.6667
1000
inf
0.2462
Framework versions
Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0
