End of training
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README.md
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---
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base_model: facebook/mms-1b-all
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datasets:
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- common_voice_17_0
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library_name: transformers
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license: cc-by-nc-4.0
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metrics:
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- wer
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- bleu
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tags:
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- generated_from_trainer
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model-index:
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- name: wav2vec2-mms-1b-CV17.0-training_set_variations
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results:
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- task:
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type: automatic-speech-recognition
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name: Automatic Speech Recognition
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dataset:
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name: common_voice_17_0
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type: common_voice_17_0
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split: validation
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args: ta
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metrics:
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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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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_17_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer: 0.
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- Cer: 0.
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- Bleu: 0.
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## Model description
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### Training results
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| Training Loss | Epoch
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| 0.1654 | 1.3672 | 1400 | 0.2028 | 0.3549 | 0.0568 | 0.4288 |
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| 0.1696 | 1.4648 | 1500 | 0.2011 | 0.3579 | 0.0567 | 0.4199 |
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| 0.1622 | 1.5625 | 1600 | 0.1999 | 0.3568 | 0.0570 | 0.4228 |
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| 0.1742 | 1.6602 | 1700 | 0.1983 | 0.3490 | 0.0559 | 0.4365 |
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| 0.1581 | 1.7578 | 1800 | 0.1973 | 0.3511 | 0.0558 | 0.4329 |
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| 0.1616 | 1.8555 | 1900 | 0.1970 | 0.3482 | 0.0556 | 0.4381 |
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| 0.1607 | 1.9531 | 2000 | 0.1970 | 0.3503 | 0.0557 | 0.4336 |
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### Framework versions
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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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datasets:
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- common_voice_17_0
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metrics:
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- wer
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- bleu
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model-index:
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- name: wav2vec2-mms-1b-CV17.0-training_set_variations
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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_17_0
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type: common_voice_17_0
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split: validation
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args: ta
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metrics:
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- name: Wer
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type: wer
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value: 0.4958060228262364
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- name: Bleu
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type: bleu
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value: 0.2629057639184852
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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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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_17_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5099
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- Wer: 0.4958
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- Cer: 0.0885
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- Bleu: 0.2629
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Bleu |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
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| 11.4061 | 50.0 | 50 | 4.6415 | 1.0007 | 0.9640 | 0.0 |
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| 1.789 | 100.0 | 100 | 0.3026 | 0.4457 | 0.0734 | 0.3064 |
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| 0.08 | 150.0 | 150 | 0.3223 | 0.4304 | 0.0711 | 0.3275 |
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| 0.0473 | 200.0 | 200 | 0.3547 | 0.4426 | 0.0742 | 0.3156 |
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| 0.0364 | 250.0 | 250 | 0.3786 | 0.4556 | 0.0761 | 0.2972 |
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| 0.0298 | 300.0 | 300 | 0.4070 | 0.4629 | 0.0800 | 0.2875 |
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| 0.0279 | 350.0 | 350 | 0.4190 | 0.4688 | 0.0799 | 0.2864 |
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| 0.0253 | 400.0 | 400 | 0.4353 | 0.4755 | 0.0818 | 0.2757 |
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| 0.0198 | 450.0 | 450 | 0.4808 | 0.5066 | 0.0887 | 0.2432 |
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| 0.0216 | 500.0 | 500 | 0.4699 | 0.4780 | 0.0815 | 0.2777 |
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| 0.0194 | 550.0 | 550 | 0.4745 | 0.4895 | 0.0877 | 0.2643 |
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| 0.0201 | 600.0 | 600 | 0.5035 | 0.4971 | 0.0881 | 0.2647 |
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| 0.0153 | 650.0 | 650 | 0.5099 | 0.4958 | 0.0885 | 0.2629 |
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### Framework versions
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adapter.tam-32.safetensors
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model.safetensors
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