End of training
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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: facebook/data2vec-audio-base-960h
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tags:
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- generated_from_trainer
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datasets:
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- minds14
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metrics:
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- wer
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model-index:
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- name: my_awesome_asr_mind_model3
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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: minds14
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type: minds14
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config: en-US
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split: train[:100]
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args: en-US
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metrics:
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- name: Wer
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type: wer
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value: 0.6055776892430279
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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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# my_awesome_asr_mind_model3
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This model is a fine-tuned version of [facebook/data2vec-audio-base-960h](https://huggingface.co/facebook/data2vec-audio-base-960h) on the minds14 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1780.6462
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- Wer: 0.6056
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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: 1e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 16
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- training_steps: 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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| No log | 1.0 | 5 | 1753.7185 | 0.6016 |
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| No log | 2.0 | 10 | 1780.6462 | 0.6056 |
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### Framework versions
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- Transformers 4.46.2
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- Pytorch 2.4.1+cu118
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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