Downloads · 30 days
3
7% of all-time downloads
SALAMA_NEWMEDTT
Mubarak127/SALAMA_NEWMEDTT
SALAMA_NEWMEDTT is a automatic speech recognition model from Mubarak127. Use it when you need speech turned into text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
45
Public
Parameters
1.5B
49.4 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors6.2 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- Model type
- whisper
- Access
- Public
- Created
- Aug 3, 2026
- Updated
- Aug 4, 2026
- SHA
- 9717d588
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
SALAMA_NEWMEDTT
This model is a fine-tuned version of Mubarak127/waxal-whisper-large-v3-lin_asr_new-app on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.6054
- eval_wer: 54.4839
- eval_runtime: 1570.5168
- eval_samples_per_second: 0.555
- eval_steps_per_second: 0.278
- epoch: 1.1606
- step: 1200
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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: 500
- num_epochs: 2
- mixed_precision_training: Native AMP
Framework versions
- Transformers 5.14.1
- Pytorch 2.5.1+cu121
- Datasets 5.0.1
- Tokenizers 0.22.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- Created
- Aug 3, 2026
- Updated
- Aug 4, 2026