| | --- |
| | license: apache-2.0 |
| | base_model: openai/whisper-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: whisper-small-lang-id |
| | results: [] |
| | --- |
| | |
| | <!-- 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-small-lang-id |
| |
|
| | This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3220 |
| | - Accuracy: 0.9555 |
| | - F1: 0.9549 |
| |
|
| | ## 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: 3e-05 |
| | - train_batch_size: 2 |
| | - eval_batch_size: 2 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 8 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - training_steps: 10000 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| |
| | | 0.0498 | 0.25 | 2500 | 0.2722 | 0.9578 | 0.9576 | |
| | | 0.0039 | 1.12 | 5000 | 0.6877 | 0.8952 | 0.8901 | |
| | | 0.0 | 1.38 | 7500 | 0.2562 | 0.9532 | 0.9526 | |
| | | 0.0 | 2.25 | 10000 | 0.3220 | 0.9555 | 0.9549 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.38.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.17.1 |
| | - Tokenizers 0.15.2 |
| |
|
