Teamim-tiny_Random-True_DropOut-0.1_WeightDecay-1e-06_Augmented_date-27-06-2024_09-48-25

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

he-cantillation

This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.1635
• Wer: 15.8869
• Avg Precision Exact: 0.8555
• Avg Recall Exact: 0.8550
• Avg F1 Exact: 0.8548
• Avg Precision Letter Shift: 0.8805
• Avg Recall Letter Shift: 0.8801
• Avg F1 Letter Shift: 0.8799
• Avg Precision Word Level: 0.8850
• Avg Recall Word Level: 0.8845
• Avg F1 Word Level: 0.8842
• Avg Precision Word Shift: 0.9658
• Avg Recall Word Shift: 0.9665
• Avg F1 Word Shift: 0.9656
• Precision Median Exact: 0.9333
• Recall Median Exact: 0.9333
• F1 Median Exact: 0.9375
• Precision Max Exact: 1.0
• Recall Max Exact: 1.0
• F1 Max Exact: 1.0
• Precision Min Exact: 0.0
• Recall Min Exact: 0.0
• F1 Min Exact: 0.0
• Precision Min Letter Shift: 0.0
• Recall Min Letter Shift: 0.0
• F1 Min Letter Shift: 0.0
• Precision Min Word Level: 0.0
• Recall Min Word Level: 0.0
• F1 Min Word Level: 0.0
• Precision Min Word Shift: 0.1429
• Recall Min Word Shift: 0.1111
• F1 Min Word Shift: 0.125

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: 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: 50
• training_steps: 20000
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.41.2
• Pytorch 2.2.1
• Datasets 2.20.0
• Tokenizers 0.19.1