End of training
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- model.safetensors +1 -1
README.md
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---
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license: mit
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---
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---
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license: mit
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base_model: facebook/w2v-bert-2.0
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_16_1
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metrics:
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- wer
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model-index:
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- name: w2v-bert-2.0-sr
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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_16_1
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type: common_voice_16_1
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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: 0.06932439583700829
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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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# w2v-bert-2.0-sr
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_16_1 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1200
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- Wer: 0.0693
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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: 4
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- eval_batch_size: 8
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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: 500
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- num_epochs: 10
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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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| 2.202 | 2.89 | 300 | 0.2028 | 0.1009 |
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| 0.1031 | 5.78 | 600 | 0.1945 | 0.1062 |
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| 0.0429 | 8.67 | 900 | 0.1200 | 0.0693 |
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### Framework versions
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- Transformers 4.37.2
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- Pytorch 2.1.2+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.1
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model.safetensors
CHANGED
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version https://git-lfs.github.com/spec/v1
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-
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size 2422958060
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version https://git-lfs.github.com/spec/v1
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size 2422958060
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