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wav2vec2-2-bart-debug – AI Model by sanchit-gandhi | AlphaNeural AI
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wav2vec2-2-bart-debug
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transformers
pytorch
tensorboard
speech-encoder-decoder
automatic-speech-recognition
generated_from_trainer
librispeech_asr
endpoints_compatible
us
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This model was trained from scratch on the librispeech_asr dataset.
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: 4
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: 1.0
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.17.0.dev0
Pytorch 1.10.2+cu113
Datasets 1.18.3
Tokenizers 0.11.0
