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README.md ADDED
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+ ---
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+ base_model: facebook/w2v-bert-2.0
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+ license: mit
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+ metrics:
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+ - wer
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: w2v-bert-2.0-nonstudio_and_studioRecords
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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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+ # w2v-bert-2.0-nonstudio_and_studioRecords
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+
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+ This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1722
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+ - Wer: 0.1299
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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: 5e-05
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+ - train_batch_size: 16
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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: 32
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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: 10
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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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+ | 1.1416 | 0.46 | 600 | 0.3393 | 0.4616 |
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+ | 0.1734 | 0.92 | 1200 | 0.2414 | 0.3493 |
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+ | 0.1254 | 1.38 | 1800 | 0.2205 | 0.2963 |
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+ | 0.1097 | 1.84 | 2400 | 0.2157 | 0.3133 |
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+ | 0.0923 | 2.3 | 3000 | 0.1854 | 0.2473 |
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+ | 0.0792 | 2.76 | 3600 | 0.1939 | 0.2471 |
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+ | 0.0696 | 3.22 | 4200 | 0.1720 | 0.2282 |
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+ | 0.0589 | 3.68 | 4800 | 0.1768 | 0.2013 |
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+ | 0.0552 | 4.14 | 5400 | 0.1635 | 0.1864 |
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+ | 0.0437 | 4.6 | 6000 | 0.1501 | 0.1826 |
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+ | 0.0408 | 5.06 | 6600 | 0.1500 | 0.1645 |
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+ | 0.0314 | 5.52 | 7200 | 0.1559 | 0.1655 |
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+ | 0.0317 | 5.98 | 7800 | 0.1448 | 0.1553 |
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+ | 0.022 | 6.44 | 8400 | 0.1592 | 0.1590 |
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+ | 0.0218 | 6.9 | 9000 | 0.1431 | 0.1458 |
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+ | 0.0154 | 7.36 | 9600 | 0.1514 | 0.1366 |
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+ | 0.0141 | 7.82 | 10200 | 0.1540 | 0.1383 |
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+ | 0.0113 | 8.28 | 10800 | 0.1558 | 0.1391 |
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+ | 0.0085 | 8.74 | 11400 | 0.1612 | 0.1356 |
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+ | 0.0072 | 9.2 | 12000 | 0.1697 | 0.1289 |
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+ | 0.0046 | 9.66 | 12600 | 0.1722 | 0.1299 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.1.1+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
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