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thunninoi
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wav2vec2-japanese-vtuber

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Inference Endpoints
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update model card README.md

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+ ---
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: checkpoints2
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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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+ # checkpoints2
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+
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+ This model was trained from scratch on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1593
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+ - Wer: 0.0579
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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: 0.0003
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+ - train_batch_size: 3
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 6
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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: 50
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+ - mixed_precision_training: Native AMP
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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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+ | 0.2075 | 1.0 | 124 | 0.1170 | 0.0525 |
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+ | 0.0978 | 2.0 | 248 | 0.0875 | 0.0507 |
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+ | 0.046 | 3.0 | 372 | 0.1017 | 0.0534 |
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+ | 0.031 | 4.0 | 496 | 0.1167 | 0.0543 |
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+ | 0.0353 | 5.0 | 620 | 0.1194 | 0.0534 |
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+ | 0.0345 | 6.0 | 744 | 0.1217 | 0.0597 |
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+ | 0.0248 | 7.0 | 868 | 0.1366 | 0.0633 |
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+ | 0.02 | 8.0 | 992 | 0.1193 | 0.0597 |
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+ | 0.0339 | 9.0 | 1116 | 0.1341 | 0.0624 |
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+ | 0.0172 | 10.0 | 1240 | 0.1200 | 0.0570 |
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+ | 0.022 | 11.0 | 1364 | 0.1323 | 0.0688 |
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+ | 0.0221 | 12.0 | 1488 | 0.1219 | 0.0543 |
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+ | 0.0168 | 13.0 | 1612 | 0.1567 | 0.0769 |
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+ | 0.0145 | 14.0 | 1736 | 0.1337 | 0.0606 |
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+ | 0.0114 | 15.0 | 1860 | 0.1299 | 0.0688 |
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+ | 0.0209 | 16.0 | 1984 | 0.1266 | 0.0661 |
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+ | 0.0183 | 17.0 | 2108 | 0.1412 | 0.0697 |
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+ | 0.0135 | 18.0 | 2232 | 0.1394 | 0.0670 |
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+ | 0.0101 | 19.0 | 2356 | 0.1429 | 0.0724 |
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+ | 0.0125 | 20.0 | 2480 | 0.1296 | 0.0733 |
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+ | 0.0102 | 21.0 | 2604 | 0.1233 | 0.0697 |
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+ | 0.006 | 22.0 | 2728 | 0.1368 | 0.0769 |
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+ | 0.0058 | 23.0 | 2852 | 0.1225 | 0.0624 |
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+ | 0.0046 | 24.0 | 2976 | 0.1220 | 0.0606 |
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+ | 0.0081 | 25.0 | 3100 | 0.1425 | 0.0751 |
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+ | 0.0088 | 26.0 | 3224 | 0.1311 | 0.0670 |
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+ | 0.0055 | 27.0 | 3348 | 0.1286 | 0.0597 |
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+ | 0.0052 | 28.0 | 3472 | 0.1228 | 0.0561 |
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+ | 0.0026 | 29.0 | 3596 | 0.1437 | 0.0606 |
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+ | 0.0052 | 30.0 | 3720 | 0.1430 | 0.0679 |
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+ | 0.0096 | 31.0 | 3844 | 0.1458 | 0.0733 |
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+ | 0.0051 | 32.0 | 3968 | 0.1393 | 0.0606 |
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+ | 0.0031 | 33.0 | 4092 | 0.1441 | 0.0633 |
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+ | 0.0042 | 34.0 | 4216 | 0.1539 | 0.0679 |
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+ | 0.0032 | 35.0 | 4340 | 0.1496 | 0.0661 |
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+ | 0.0035 | 36.0 | 4464 | 0.1486 | 0.0615 |
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+ | 0.0017 | 37.0 | 4588 | 0.1489 | 0.0643 |
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+ | 0.0021 | 38.0 | 4712 | 0.1583 | 0.0615 |
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+ | 0.0031 | 39.0 | 4836 | 0.1544 | 0.0597 |
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+ | 0.0021 | 40.0 | 4960 | 0.1638 | 0.0633 |
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+ | 0.0017 | 41.0 | 5084 | 0.1630 | 0.0633 |
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+ | 0.0013 | 42.0 | 5208 | 0.1618 | 0.0561 |
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+ | 0.0015 | 43.0 | 5332 | 0.1656 | 0.0597 |
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+ | 0.0015 | 44.0 | 5456 | 0.1662 | 0.0588 |
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+ | 0.0018 | 45.0 | 5580 | 0.1594 | 0.0597 |
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+ | 0.0007 | 46.0 | 5704 | 0.1603 | 0.0597 |
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+ | 0.0005 | 47.0 | 5828 | 0.1614 | 0.0615 |
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+ | 0.0011 | 48.0 | 5952 | 0.1599 | 0.0579 |
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+ | 0.0007 | 49.0 | 6076 | 0.1601 | 0.0579 |
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+ | 0.0009 | 50.0 | 6200 | 0.1593 | 0.0579 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.17.0
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+ - Pytorch 1.11.0+cu113
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+ - Datasets 1.18.3
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+ - Tokenizers 0.12.1