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w2v-bert-2.0_luo_v2_farmerline – AI Model by ghananlpcommunity | AlphaNeural AI
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w2v-bert-2.0_luo_v2_farmerline
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transformers
tensorboard
safetensors
wav2vec2-bert
automatic-speech-recognition
generated_from_trainer
FarmerlineML/w2v-bert-2.0_luo
finetune
endpoints_compatible
us
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w2v-bert-2.0_luo_v2
This model is a fine-tuned version of
FarmerlineML/w2v-bert-2.0_luo
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 0.2904
eval_cer: 0.0688
eval_wer: 0.3058
eval_runtime: 30.6283
eval_samples_per_second: 36.861
eval_steps_per_second: 4.636
epoch: 2.1416
step: 3600
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: 0.0001
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
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 4.52.4
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.1
