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--- |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-1b |
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tags: |
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- generated_from_trainer |
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datasets: |
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- audiofolder |
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metrics: |
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- wer |
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model-index: |
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- name: results |
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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: audiofolder |
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type: audiofolder |
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config: default |
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split: test |
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args: default |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.5377405032067094 |
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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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# results |
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This model is a fine-tuned version of [facebook/mms-1b](https://huggingface.co/facebook/mms-1b) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3647 |
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- Wer: 0.5377 |
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- Cer: 0.2651 |
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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: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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: 500 |
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- num_epochs: 13 |
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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 | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:|:------:| |
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| 3.4128 | 1.6495 | 40 | 3.2154 | 1.0 | 1.0 | |
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| 2.8944 | 3.2990 | 80 | 2.7463 | 0.9896 | 0.9891 | |
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| 1.5023 | 4.9485 | 120 | 1.4803 | 0.6971 | 0.3166 | |
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| 1.1458 | 6.5979 | 160 | 1.2789 | 0.5580 | 0.2638 | |
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| 0.9619 | 8.2474 | 200 | 1.2553 | 0.5639 | 0.2702 | |
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| 0.8777 | 9.8969 | 240 | 1.2722 | 0.5215 | 0.2633 | |
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| 0.7732 | 11.5464 | 280 | 1.3647 | 0.5377 | 0.2651 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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