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README.md
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---
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license: apache-2.0
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base_model: facebook/wav2vec2-large-lv60
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tags:
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- generated_from_trainer
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datasets:
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- ami
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metrics:
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- wer
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model-index:
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- name: wav2vec2-base-ami-fine-tuned
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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: ami
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type: ami
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config: ihm
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split: None
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args: ihm
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metrics:
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- name: Wer
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type: wer
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value: 0.31977176615593855
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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-base-ami-fine-tuned
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This model is a fine-tuned version of [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) on the ami dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5417
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- Wer: 0.3198
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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: 0.0001
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- train_batch_size: 16
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- eval_batch_size: 16
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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: linear
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 2.0
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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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| 1.0732 | 0.1565 | 1000 | 1.1351 | 0.6738 |
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| 1.4052 | 0.3131 | 2000 | 0.7311 | 0.4083 |
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| 0.8798 | 0.4696 | 3000 | 0.5889 | 0.3604 |
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| 0.4789 | 0.6262 | 4000 | 0.5681 | 0.3521 |
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| 0.8011 | 0.7827 | 5000 | 0.5288 | 0.3382 |
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| 1.4331 | 0.9393 | 6000 | 0.5386 | 0.3280 |
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| 0.2201 | 1.0958 | 7000 | 0.5154 | 0.3198 |
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| 0.1934 | 1.2523 | 8000 | 0.4895 | 0.3131 |
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| 0.2713 | 1.4089 | 9000 | 0.4809 | 0.3065 |
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| 0.1388 | 1.5654 | 10000 | 0.4984 | 0.3061 |
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| 0.4085 | 1.7220 | 11000 | 0.4842 | 0.3082 |
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| 0.3529 | 1.8785 | 12000 | 0.5417 | 0.3198 |
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### Framework versions
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- Transformers 4.42.0.dev0
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- Pytorch 2.3.0a0+gitcd033a1
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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