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models_sv_eric_1

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
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+ ---
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+ license: cc-by-nc-4.0
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: models_sv_eric_1
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+ results: []
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+ ---
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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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+
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+ # models_sv_eric_1
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.1340
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+ - Wer: 0.6241
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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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: 300
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:------:|:-----:|:---------------:|:------:|
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+ | 27.2483 | 5.81 | 250 | 12.8968 | 1.0 |
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+ | 5.3813 | 11.63 | 500 | 3.7635 | 1.0 |
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+ | 3.1776 | 17.44 | 750 | 3.1586 | 1.0 |
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+ | 3.0849 | 23.26 | 1000 | 3.1336 | 1.0 |
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+ | 3.0351 | 29.07 | 1250 | 3.0069 | 1.0 |
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+ | 2.5591 | 34.88 | 1500 | 1.8101 | 0.9735 |
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+ | 1.4236 | 40.7 | 1750 | 1.3666 | 0.8120 |
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+ | 0.9233 | 46.51 | 2000 | 1.3338 | 0.7470 |
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+ | 0.6594 | 52.33 | 2250 | 1.4020 | 0.7060 |
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+ | 0.5056 | 58.14 | 2500 | 1.3793 | 0.7036 |
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+ | 0.4135 | 63.95 | 2750 | 1.3789 | 0.6988 |
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+ | 0.3521 | 69.77 | 3000 | 1.4288 | 0.6795 |
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+ | 0.2728 | 75.58 | 3250 | 1.4819 | 0.6554 |
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+ | 0.2419 | 81.4 | 3500 | 1.5370 | 0.6602 |
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+ | 0.2288 | 87.21 | 3750 | 1.4477 | 0.6265 |
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+ | 0.2009 | 93.02 | 4000 | 1.5387 | 0.6602 |
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+ | 0.1773 | 98.84 | 4250 | 1.6789 | 0.6723 |
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+ | 0.1701 | 104.65 | 4500 | 1.6322 | 0.6361 |
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+ | 0.1562 | 110.47 | 4750 | 1.5988 | 0.6554 |
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+ | 0.1433 | 116.28 | 5000 | 1.7502 | 0.6458 |
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+ | 0.1373 | 122.09 | 5250 | 1.7735 | 0.6217 |
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+ | 0.1186 | 127.91 | 5500 | 1.7193 | 0.6193 |
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+ | 0.1127 | 133.72 | 5750 | 1.8742 | 0.6410 |
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+ | 0.113 | 139.53 | 6000 | 1.8339 | 0.6337 |
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+ | 0.1106 | 145.35 | 6250 | 1.7486 | 0.6289 |
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+ | 0.0955 | 151.16 | 6500 | 1.7455 | 0.6361 |
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+ | 0.0934 | 156.98 | 6750 | 1.8922 | 0.6361 |
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+ | 0.0873 | 162.79 | 7000 | 2.0495 | 0.6530 |
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+ | 0.0863 | 168.6 | 7250 | 1.8438 | 0.6361 |
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+ | 0.0901 | 174.42 | 7500 | 2.0441 | 0.6289 |
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+ | 0.0749 | 180.23 | 7750 | 2.0112 | 0.6265 |
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+ | 0.0887 | 186.05 | 8000 | 2.0684 | 0.6554 |
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+ | 0.074 | 191.86 | 8250 | 2.0821 | 0.6265 |
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+ | 0.0714 | 197.67 | 8500 | 2.0790 | 0.6313 |
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+ | 0.0638 | 203.49 | 8750 | 2.0158 | 0.6072 |
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+ | 0.0633 | 209.3 | 9000 | 2.0423 | 0.6386 |
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+ | 0.0621 | 215.12 | 9250 | 2.0013 | 0.6241 |
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+ | 0.0616 | 220.93 | 9500 | 1.9567 | 0.6386 |
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+ | 0.0627 | 226.74 | 9750 | 2.0302 | 0.6361 |
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+ | 0.0604 | 232.56 | 10000 | 2.0424 | 0.6096 |
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+ | 0.0551 | 238.37 | 10250 | 2.0238 | 0.6096 |
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+ | 0.0559 | 244.19 | 10500 | 2.0207 | 0.6361 |
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+ | 0.0587 | 250.0 | 10750 | 2.0818 | 0.6361 |
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+ | 0.0508 | 255.81 | 11000 | 2.1106 | 0.6289 |
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+ | 0.0494 | 261.63 | 11250 | 2.1194 | 0.6434 |
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+ | 0.0576 | 267.44 | 11500 | 2.0752 | 0.6410 |
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+ | 0.0521 | 273.26 | 11750 | 2.1455 | 0.6361 |
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+ | 0.0479 | 279.07 | 12000 | 2.1583 | 0.6337 |
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+ | 0.0501 | 284.88 | 12250 | 2.1400 | 0.6386 |
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+ | 0.0447 | 290.7 | 12500 | 2.1440 | 0.6265 |
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+ | 0.0455 | 296.51 | 12750 | 2.1340 | 0.6241 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.11.3
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+ - Pytorch 1.9.0
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+ - Datasets 1.13.3
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+ - Tokenizers 0.10.3