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--- |
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library_name: transformers |
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language: |
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- tg |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Tajik |
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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: Google Fleurs |
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type: google/fleurs |
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config: tg_tj |
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split: None |
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args: 'config: tg, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 24.260635774157837 |
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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 Tajik |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Google Fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4141 |
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- Wer: 24.2606 |
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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: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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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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| 2.7687 | 1.0 | 79 | 0.5778 | 39.6568 | |
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| 0.7193 | 2.0 | 158 | 0.3890 | 28.3568 | |
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| 0.3659 | 3.0 | 237 | 0.3611 | 26.0636 | |
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| 0.2021 | 4.0 | 316 | 0.3629 | 25.1068 | |
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| 0.1099 | 5.0 | 395 | 0.3740 | 25.3044 | |
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| 0.0597 | 6.0 | 474 | 0.3887 | 24.3081 | |
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| 0.0339 | 7.0 | 553 | 0.4005 | 24.6639 | |
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| 0.0213 | 8.0 | 632 | 0.4082 | 24.3239 | |
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| 0.0158 | 9.0 | 711 | 0.4131 | 24.2685 | |
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| 0.014 | 10.0 | 790 | 0.4141 | 24.2606 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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