cantillation/whisper-medium-he-teamim-allNusah-12-03-24-warmup-100

he

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: 0.1270
• eval_wer: 12.6053
• eval_avg_precision_Exact: 0.9036
• eval_avg_recall_Exact: 0.9073
• eval_avg_f1_Exact: 0.9050
• eval_avg_precision_Letter_Shift: 0.9228
• eval_avg_recall_Letter_Shift: 0.9267
• eval_avg_f1_Letter_Shift: 0.9243
• eval_avg_precision_Word_Level: 0.9247
• eval_avg_recall_Word_Level: 0.9284
• eval_avg_f1_Word_Level: 0.9261
• eval_avg_precision_Word_Shift: 0.9717
• eval_avg_recall_Word_Shift: 0.9751
• eval_avg_f1_Word_Shift: 0.9729
• eval_precision_median_exact: 1.0
• eval_recall_median_exact: 1.0
• eval_f1_median_exact: 0.9677
• 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: 0.1429
• eval_recall_min_Word_Shift: 0.1111
• eval_f1_min_Word_Shift: 0.125
• eval_runtime: 1560.6561
• eval_samples_per_second: 1.725
• eval_steps_per_second: 0.054
• epoch: 0.8
• step: 10000

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