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--- |
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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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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-base-timit-demo-google-colab-Ezra_William |
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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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# wav2vec2-base-timit-demo-google-colab-Ezra_William |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5198 |
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- Wer: 0.3335 |
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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: 8 |
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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: 1000 |
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- num_epochs: 30 |
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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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| 3.4828 | 1.0 | 500 | 1.6354 | 1.0429 | |
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| 0.8406 | 2.01 | 1000 | 0.5389 | 0.5405 | |
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| 0.4345 | 3.01 | 1500 | 0.4202 | 0.4438 | |
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| 0.2912 | 4.02 | 2000 | 0.4195 | 0.4216 | |
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| 0.2316 | 5.02 | 2500 | 0.4253 | 0.4051 | |
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| 0.1917 | 6.02 | 3000 | 0.3969 | 0.3958 | |
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| 0.1545 | 7.03 | 3500 | 0.4291 | 0.3912 | |
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| 0.1423 | 8.03 | 4000 | 0.4349 | 0.3731 | |
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| 0.1234 | 9.04 | 4500 | 0.4419 | 0.3784 | |
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| 0.1124 | 10.04 | 5000 | 0.4713 | 0.3741 | |
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| 0.0991 | 11.04 | 5500 | 0.4711 | 0.3692 | |
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| 0.0924 | 12.05 | 6000 | 0.4994 | 0.3699 | |
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| 0.0809 | 13.05 | 6500 | 0.4888 | 0.3643 | |
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| 0.0715 | 14.06 | 7000 | 0.4828 | 0.3634 | |
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| 0.0646 | 15.06 | 7500 | 0.5058 | 0.3570 | |
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| 0.0604 | 16.06 | 8000 | 0.5586 | 0.3637 | |
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| 0.0571 | 17.07 | 8500 | 0.4991 | 0.3553 | |
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| 0.0532 | 18.07 | 9000 | 0.5317 | 0.3566 | |
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| 0.0471 | 19.08 | 9500 | 0.5308 | 0.3508 | |
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| 0.0449 | 20.08 | 10000 | 0.5362 | 0.3486 | |
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| 0.0373 | 21.08 | 10500 | 0.5211 | 0.3479 | |
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| 0.0351 | 22.09 | 11000 | 0.5132 | 0.3445 | |
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| 0.0333 | 23.09 | 11500 | 0.4927 | 0.3381 | |
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| 0.0302 | 24.1 | 12000 | 0.5330 | 0.3413 | |
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| 0.0282 | 25.1 | 12500 | 0.5295 | 0.3396 | |
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| 0.024 | 26.1 | 13000 | 0.5022 | 0.3356 | |
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| 0.0262 | 27.11 | 13500 | 0.5320 | 0.3329 | |
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| 0.0242 | 28.11 | 14000 | 0.5133 | 0.3326 | |
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| 0.0201 | 29.12 | 14500 | 0.5198 | 0.3335 | |
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### Framework versions |
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- Transformers 4.32.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 1.18.3 |
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- Tokenizers 0.13.3 |
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