metadata

library_name: transformers
license: mit
base_model: distil-whisper/distil-large-v3.5
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: >-
      Teamim-distil-large-v3.5_WeightDecay-0.005_Augmented__WithSRT_LR-1e-05_date-10-06-2025
    results: []

Teamim-distil-large-v3.5_WeightDecay-0.005_Augmented__WithSRT_LR-1e-05_date-10-06-2025

This model is a fine-tuned version of distil-whisper/distil-large-v3.5 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.7945
Wer: 68.9512
Avg Precision Exact: 0.2622
Avg Recall Exact: 0.2502
Avg F1 Exact: 0.2513
Avg Precision Letter Shift: 0.2922
Avg Recall Letter Shift: 0.2803
Avg F1 Letter Shift: 0.2796
Avg Precision Word Level: 0.3129
Avg Recall Word Level: 0.3458
Avg F1 Word Level: 0.3227
Avg Precision Word Shift: 0.5277
Avg Recall Word Shift: 0.5512
Avg F1 Word Shift: 0.5260
Precision Median Exact: 0.1429
Recall Median Exact: 0.1379
F1 Median Exact: 0.1333
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: 0.0
Recall Min Word Shift: 0.0
F1 Min Word Shift: 0.0

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: 16
eval_batch_size: 2
seed: 42
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: 100
training_steps: 10000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Avg Precision Exact	Avg Recall Exact	Avg F1 Exact	Avg Precision Letter Shift	Avg Recall Letter Shift	Avg F1 Letter Shift	Avg Precision Word Level	Avg Recall Word Level	Avg F1 Word Level	Avg Precision Word Shift	Avg Recall Word Shift	Avg F1 Word Shift	Precision Median Exact	Recall Median Exact	F1 Median Exact	Precision Max Exact	Recall Max Exact	F1 Max Exact	Precision Min Exact	Recall Min Exact	F1 Min Exact	Precision Min Letter Shift	Recall Min Letter Shift	F1 Min Letter Shift	Precision Min Word Level	Recall Min Word Level	F1 Min Word Level	Precision Min Word Shift	Recall Min Word Shift	F1 Min Word Shift
No log	0.0001	1	12.1921	169.3043	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
0.096	0.5925	5000	0.9503	76.8918	0.1974	0.2042	0.1981	0.2302	0.2405	0.2312	0.2519	0.2806	0.2607	0.4684	0.5193	0.4828	0.1071	0.1111	0.1053	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
0.0614	1.1850	10000	0.7945	68.9512	0.2622	0.2502	0.2513	0.2922	0.2803	0.2796	0.3129	0.3458	0.3227	0.5277	0.5512	0.5260	0.1429	0.1379	0.1333	1.0	1.0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

Framework versions

Transformers 4.49.0
Pytorch 2.7.0+cu126
Datasets 2.12.0
Tokenizers 0.20.1