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--- |
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base_model: mohammadsp99/whisper-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper-small-FullFinetuning-CV-train-test |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: common_voice_13_0 |
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type: common_voice_13_0 |
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config: fa |
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split: test |
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args: fa |
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metrics: |
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- name: Wer |
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type: wer |
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value: 93.93939393939394 |
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language: |
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- fa |
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library_name: adapter-transformers |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper-small-FullFinetuning-CV-train-test |
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This model is a fine-tuned version of [mohammadsp99/whisper-small](https://huggingface.co/mohammadsp99/whisper-small) on the common_voice_13_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4865 |
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- Wer: 37.3 |
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The evaluation was done after training |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 2000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.886 | 0.05 | 100 | 2.1958 | 101.5152 | |
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| 0.6142 | 0.1 | 200 | 2.2113 | 110.6061 | |
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| 0.5544 | 0.15 | 300 | 2.2247 | 215.1515 | |
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| 0.4809 | 0.2 | 400 | 1.8149 | 104.5455 | |
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| 0.393 | 0.25 | 500 | 1.8802 | 96.9697 | |
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| 0.4191 | 0.3 | 600 | 1.9056 | 107.5758 | |
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| 0.3515 | 0.35 | 700 | 1.9166 | 89.3939 | |
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| 0.2671 | 0.4 | 800 | 1.9010 | 86.3636 | |
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| 0.2763 | 0.45 | 900 | 1.8574 | 96.9697 | |
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| 0.2896 | 0.5 | 1000 | 1.8940 | 95.4545 | |
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| 0.2201 | 0.55 | 1100 | 1.6264 | 96.9697 | |
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| 0.1937 | 0.6 | 1200 | 1.8990 | 98.4848 | |
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| 0.1787 | 0.65 | 1300 | 1.7999 | 100.0 | |
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| 0.1138 | 0.7 | 1400 | 1.8118 | 96.9697 | |
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| 0.1759 | 0.75 | 1500 | 1.9026 | 93.9394 | |
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| 0.1276 | 0.8 | 1600 | 1.8715 | 195.4545 | |
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| 0.1437 | 0.85 | 1700 | 1.7353 | 92.4242 | |
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| 0.1593 | 1.02 | 1800 | 1.7307 | 95.4545 | |
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| 0.1617 | 1.07 | 1900 | 1.7732 | 96.9697 | |
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| 0.1737 | 1.12 | 2000 | 1.7646 | 93.9394 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.3 |
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- Tokenizers 0.13.3 |
