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adapter_freezed_base_const_lr_1-e3_batch32 – AI Model by LevonHakobyan | AlphaNeural AI
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adapter_freezed_base_const_lr_1-e3_batch32
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transformers
tensorboard
safetensors
wav2vec2-bert
automatic-speech-recognition
generated_from_trainer
common_voice_17_0
facebook/w2v-bert-2.0
finetune
mit
model-index
endpoints_compatible
us
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adapter_freezed_base_const_lr_1-e3_batch32
This model is a fine-tuned version of
facebook/w2v-bert-2.0
on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
Loss: 1.0721
Wer: 0.9351
Cer: 0.2622
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: 0.001
train_batch_size: 32
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
num_epochs: 10
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
Cer
0.7435
3.0769
500
0.8858
0.9372
0.2669
0.5367
6.1538
1000
0.8872
0.9318
0.2544
0.3519
9.2308
1500
1.0721
0.9351
0.2622
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
