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w2v-bert-2.0_somali_alpha_farmerline – AI Model by ghananlpcommunity | AlphaNeural AI
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w2v-bert-2.0_somali_alpha_farmerline
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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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w2v-bert-2.0_somali_alpha
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:
eval_loss: inf
eval_cer: 0.1080
eval_wer: 0.3958
eval_runtime: 39.932
eval_samples_per_second: 10.192
eval_steps_per_second: 1.277
epoch: 10.3448
step: 600
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: 1e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Use OptimizerNames.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_steps: 800
num_epochs: 16
mixed_precision_training: Native AMP
Framework versions
Transformers 4.53.3
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.2
