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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base-960h |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vecvanilla_load_best |
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results: [] |
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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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# wav2vecvanilla_load_best |
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- best model at 1400 steps, training loss 0.871600, validation loss 0.835038, evaluation WER 0.324867 |
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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: 4 |
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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: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 20 |
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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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| 1.47 | 0.43 | 100 | 1.0582 | 0.4027 | |
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| 1.2584 | 0.85 | 200 | 0.9775 | 0.3719 | |
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| 1.1377 | 1.28 | 300 | 0.9759 | 0.3628 | |
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| 1.0955 | 1.71 | 400 | 1.1271 | 0.3626 | |
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| 1.0945 | 2.14 | 500 | 0.9063 | 0.3589 | |
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| 1.0567 | 2.56 | 600 | 0.9288 | 0.3564 | |
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| 1.033 | 2.99 | 700 | 1.1634 | 0.3522 | |
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| 1.0043 | 3.42 | 800 | 0.8396 | 0.3506 | |
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| 0.9776 | 3.85 | 900 | 0.8654 | 0.3437 | |
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| 0.9147 | 4.27 | 1000 | 0.8816 | 0.3362 | |
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| 0.9041 | 4.7 | 1100 | 0.8994 | 0.3303 | |
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| 0.8648 | 5.13 | 1200 | 0.8379 | 0.3361 | |
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| 0.8241 | 5.56 | 1300 | 0.8263 | 0.3292 | |
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| 0.8716 | 5.98 | 1400 | 0.8350 | 0.3249 | |
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| 0.8218 | 6.41 | 1500 | nan | 1.0 | |
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| 0.0 | 6.84 | 1600 | nan | 1.0 | |
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| 0.0 | 7.26 | 1700 | nan | 1.0 | |
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| 0.0 | 7.69 | 1800 | nan | 1.0 | |
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| 0.0 | 8.12 | 1900 | nan | 1.0 | |
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| 0.0 | 8.55 | 2000 | nan | 1.0 | |
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| 0.0 | 8.97 | 2100 | nan | 1.0 | |
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| 0.0 | 9.4 | 2200 | nan | 1.0 | |
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| 0.0 | 9.83 | 2300 | nan | 1.0 | |
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| 0.0 | 10.26 | 2400 | nan | 1.0 | |
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| 0.0 | 10.68 | 2500 | nan | 1.0 | |
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| 0.0 | 11.11 | 2600 | nan | 1.0 | |
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| 0.0 | 11.54 | 2700 | nan | 1.0 | |
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| 0.0 | 11.97 | 2800 | nan | 1.0 | |
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| 0.0 | 12.39 | 2900 | nan | 1.0 | |
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| 0.0 | 12.82 | 3000 | nan | 1.0 | |
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| 0.0 | 13.25 | 3100 | nan | 1.0 | |
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| 0.0 | 13.68 | 3200 | nan | 1.0 | |
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| 0.0 | 14.1 | 3300 | nan | 1.0 | |
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| 0.0 | 14.53 | 3400 | nan | 1.0 | |
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| 0.0 | 14.96 | 3500 | nan | 1.0 | |
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| 0.0 | 15.38 | 3600 | nan | 1.0 | |
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| 0.0 | 15.81 | 3700 | nan | 1.0 | |
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| 0.0 | 16.24 | 3800 | nan | 1.0 | |
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| 0.0 | 16.67 | 3900 | nan | 1.0 | |
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| 0.0 | 17.09 | 4000 | nan | 1.0 | |
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| 0.0 | 17.52 | 4100 | nan | 1.0 | |
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| 0.0 | 17.95 | 4200 | nan | 1.0 | |
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| 0.0 | 18.38 | 4300 | nan | 1.0 | |
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| 0.0 | 18.8 | 4400 | nan | 1.0 | |
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| 0.0 | 19.23 | 4500 | nan | 1.0 | |
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| 0.0 | 19.66 | 4600 | nan | 1.0 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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