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--- |
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language: |
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- sr |
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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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- mozilla-foundation/common_voice_13_0 |
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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 cmb |
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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 |
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type: mozilla-foundation/common_voice_13_0 |
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config: sr |
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split: test |
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args: sr |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.13531711555169418 |
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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 Combined |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1934 |
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- Wer Ortho: 0.2322 |
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- Wer: 0.1353 |
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## Model description |
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This is a fine tunned on merged datasets Common Voice 13 + Fleurs + [Juzne vesti (South news)](http://hdl.handle.net/11356/1679) |
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Rupnik, Peter and Ljubešić, Nikola, 2022,\ |
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ASR training dataset for Serbian JuzneVesti-SR v1.0, Slovenian language resource repository CLARIN.SI, ISSN 2820-4042,\ |
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http://hdl.handle.net/11356/1679. |
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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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- 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: 1500 |
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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 Ortho | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
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| 0.4708 | 0.48 | 500 | 0.2275 | 0.2704 | 0.1738 | |
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| 0.4678 | 0.95 | 1000 | 0.1979 | 0.24 | 0.1457 | |
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| 0.3271 | 1.43 | 1500 | 0.1934 | 0.2322 | 0.1353 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
