End of training
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README.md
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---
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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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- mozilla-foundation/common_voice_13_0
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metrics:
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- wer
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model-index:
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- name: wav2vec2-large-mms-1b-por
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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: mozilla-foundation/common_voice_13_0
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type: mozilla-foundation/common_voice_13_0
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config: pt
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split: test
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args: pt
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metrics:
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- name: Wer
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type: wer
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value: 0.11407164830802818
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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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# wav2vec2-large-mms-1b-por
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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 mozilla-foundation/common_voice_13_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1340
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- Wer: 0.1141
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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: 5e-05
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- train_batch_size: 32
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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: constant_with_warmup
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- lr_scheduler_warmup_steps: 100
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- training_steps: 2500
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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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| 0.3219 | 0.55 | 500 | 0.1743 | 0.1302 |
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| 0.2443 | 1.1 | 1000 | 0.1480 | 0.1206 |
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| 0.2358 | 1.65 | 1500 | 0.1402 | 0.1167 |
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| 0.223 | 2.21 | 2000 | 0.1364 | 0.1159 |
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| 0.2213 | 2.76 | 2500 | 0.1340 | 0.1141 |
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### Framework versions
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- Transformers 4.35.0.dev0
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- Pytorch 2.1.0+cu121
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- Datasets 2.14.5
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- Tokenizers 0.14.1
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