Translation
Transformers
TensorBoard
Safetensors
Arabic
English
whisper
automatic-speech-recognition
egyptian-arabic
code-switching
Generated from Trainer
Eval Results (legacy)
Instructions to use AssemGamal955/OUTPUT_DIR3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AssemGamal955/OUTPUT_DIR3 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="AssemGamal955/OUTPUT_DIR3")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("AssemGamal955/OUTPUT_DIR3") model = AutoModelForSpeechSeq2Seq.from_pretrained("AssemGamal955/OUTPUT_DIR3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| library_name: transformers | |
| language: | |
| - ar | |
| - en | |
| license: apache-2.0 | |
| base_model: openai/whisper-medium | |
| tags: | |
| - whisper | |
| - egyptian-arabic | |
| - translation | |
| - code-switching | |
| - generated_from_trainer | |
| datasets: | |
| - Assemgamal955/egyptian-english-translation | |
| metrics: | |
| - bleu | |
| model-index: | |
| - name: Whisper Medium Egyptian Arabic --> english Translation | |
| results: | |
| - task: | |
| name: Automatic Speech Recognition | |
| type: automatic-speech-recognition | |
| dataset: | |
| name: Assemgamal955/egyptian-english-translation | |
| type: Assemgamal955/egyptian-english-translation | |
| metrics: | |
| - name: Bleu | |
| type: bleu | |
| value: 17.93015613103953 | |
| <!-- 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. --> | |
| # Whisper Medium Egyptian Arabic --> english Translation | |
| This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Assemgamal955/egyptian-english-translation dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.0574 | |
| - Model Preparation Time: 0.0101 | |
| - Bleu: 17.9302 | |
| ## 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: 7e-06 | |
| - train_batch_size: 4 | |
| - eval_batch_size: 4 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 4 | |
| - 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: cosine | |
| - lr_scheduler_warmup_steps: 500 | |
| - num_epochs: 1 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Bleu | | |
| |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:-------:| | |
| | 1.3837 | 1.0 | 1250 | 1.0422 | 0.0101 | 21.3456 | | |
| ### Framework versions | |
| - Transformers 4.53.3 | |
| - Pytorch 2.6.0+cu124 | |
| - Datasets 3.6.0 | |
| - Tokenizers 0.21.2 | |