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whisper-medium-he-teamim-allNusah-13-03-24-warmup-100-RandomFalse – AI Model by cantillation | AlphaNeural AI
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cantillation
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whisper-medium-he-teamim-allNusah-13-03-24-warmup-100-RandomFalse
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
he
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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This model is a fine-tuned version of
openai/whisper-medium
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 0.7434
eval_wer: 12.1548
eval_avg_precision_Exact: 0.9045
eval_avg_recall_Exact: 0.9047
eval_avg_f1_Exact: 0.9042
eval_avg_precision_Letter_Shift: 0.9263
eval_avg_recall_Letter_Shift: 0.9265
eval_avg_f1_Letter_Shift: 0.9260
eval_avg_precision_Word_Level: 0.9288
eval_avg_recall_Word_Level: 0.9291
eval_avg_f1_Word_Level: 0.9285
eval_avg_precision_Word_Shift: 0.9744
eval_avg_recall_Word_Shift: 0.9757
eval_avg_f1_Word_Shift: 0.9746
eval_precision_median_exact: 1.0
eval_recall_median_exact: 1.0
eval_f1_median_exact: 1.0
eval_precision_max_exact: 1.0
eval_recall_max_exact: 1.0
eval_f1_max_exact: 1.0
eval_precision_min_Exact: 0.0
eval_recall_min_Exact: 0.0
eval_f1_min_Exact: 0.0
eval_precision_min_Letter_Shift: 0.0
eval_recall_min_Letter_Shift: 0.0
eval_f1_min_Letter_Shift: 0.0
eval_precision_min_Word_Level: 0.0
eval_recall_min_Word_Level: 0.0
eval_f1_min_Word_Level: 0.0
eval_precision_min_Word_Shift: 0.0
eval_recall_min_Word_Shift: 0.0
eval_f1_min_Word_Shift: 0.0
eval_runtime: 1534.2005
eval_samples_per_second: 1.755
eval_steps_per_second: 0.055
step: 0
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: 8
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
training_steps: 30000
mixed_precision_training: Native AMP
Framework versions
Transformers 4.39.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.16.1
Tokenizers 0.15.0
