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--- |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-1b-all |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: mms_kik |
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results: [] |
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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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# mms_kik |
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: inf |
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- Wer: 0.1756 |
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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: 0.001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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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: 100 |
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- num_epochs: 4 |
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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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| 4.4384 | 0.1576 | 100 | inf | 0.4287 | |
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| 0.5264 | 0.3152 | 200 | inf | 0.3938 | |
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| 0.4716 | 0.4728 | 300 | inf | 0.3655 | |
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| 0.4084 | 0.6304 | 400 | inf | 0.3319 | |
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| 0.3953 | 0.7880 | 500 | inf | 0.3340 | |
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| 0.3605 | 0.9456 | 600 | inf | 0.3109 | |
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| 0.3601 | 1.1032 | 700 | inf | 0.2919 | |
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| 0.3368 | 1.2608 | 800 | inf | 0.2746 | |
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| 0.3102 | 1.4184 | 900 | inf | 0.2691 | |
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| 0.3209 | 1.5760 | 1000 | inf | 0.2602 | |
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| 0.2975 | 1.7336 | 1100 | inf | 0.2488 | |
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| 0.2741 | 1.8913 | 1200 | inf | 0.2356 | |
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| 0.271 | 2.0489 | 1300 | inf | 0.2297 | |
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| 0.2494 | 2.2065 | 1400 | inf | 0.2233 | |
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| 0.254 | 2.3641 | 1500 | inf | 0.2110 | |
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| 0.2484 | 2.5217 | 1600 | inf | 0.2117 | |
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| 0.2416 | 2.6793 | 1700 | inf | 0.2020 | |
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| 0.2366 | 2.8369 | 1800 | inf | 0.1985 | |
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| 0.2313 | 2.9945 | 1900 | inf | 0.1959 | |
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| 0.2228 | 3.1521 | 2000 | inf | 0.1897 | |
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| 0.2138 | 3.3097 | 2100 | inf | 0.1868 | |
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| 0.2116 | 3.4673 | 2200 | inf | 0.1822 | |
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| 0.223 | 3.6249 | 2300 | inf | 0.1788 | |
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| 0.2144 | 3.7825 | 2400 | inf | 0.1774 | |
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| 0.2131 | 3.9401 | 2500 | inf | 0.1756 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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