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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/wav2vec2-base |
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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: wav2vec2-minds14-en |
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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: None |
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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: 1.0 |
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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-minds14-en |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 5.5729 |
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- Wer: 1.0 |
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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: 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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- training_steps: 2000 |
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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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| 5.3811 | 3.5088 | 100 | 6.8598 | 1.0006 | |
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| 4.9442 | 7.0175 | 200 | 6.6217 | 1.0018 | |
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| 4.6255 | 10.5263 | 300 | 6.2050 | 1.0 | |
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| 4.4037 | 14.0351 | 400 | 6.1160 | 1.0 | |
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| 4.1672 | 17.5439 | 500 | 5.7863 | 1.0 | |
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| 3.8786 | 21.0526 | 600 | 5.6219 | 1.0 | |
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| 3.6182 | 24.5614 | 700 | 5.4987 | 1.0 | |
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| 3.654 | 28.0702 | 800 | 5.6024 | 1.0 | |
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| 3.4135 | 31.5789 | 900 | 5.5648 | 1.0 | |
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| 3.3532 | 35.0877 | 1000 | 5.6507 | 1.0 | |
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| 3.344 | 38.5965 | 1100 | 5.5189 | 1.0 | |
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| 3.3233 | 42.1053 | 1200 | 5.6830 | 1.0 | |
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| 3.3983 | 45.6140 | 1300 | 5.5447 | 1.0 | |
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| 3.2433 | 49.1228 | 1400 | 5.5065 | 1.0 | |
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| 3.2082 | 52.6316 | 1500 | 5.4783 | 1.0 | |
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| 3.1958 | 56.1404 | 1600 | 5.5747 | 1.0 | |
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| 3.1756 | 59.6491 | 1700 | 5.5580 | 1.0 | |
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| 3.1757 | 63.1579 | 1800 | 5.5556 | 1.0 | |
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| 3.1758 | 66.6667 | 1900 | 5.6747 | 1.0 | |
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| 3.1373 | 70.1754 | 2000 | 5.5729 | 1.0 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.5.0+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.19.1 |
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