| ---
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| library_name: transformers
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| license: apache-2.0
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| base_model: facebook/wav2vec2-lv-60-espeak-cv-ft
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| tags:
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| - generated_from_trainer
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| model-index:
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| - name: wav2vec2-lv-60-espeak-cv-ft-custom_vocab-OtherDiacritics-ds-f4
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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-lv-60-espeak-cv-ft-custom_vocab-OtherDiacritics-ds-f4
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| This model is a fine-tuned version of [facebook/wav2vec2-lv-60-espeak-cv-ft](https://huggingface.co/facebook/wav2vec2-lv-60-espeak-cv-ft) on an unknown dataset.
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| It achieves the following results on the evaluation set:
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| - Loss: 0.2274
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| - Per: 0.2720
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|
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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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|
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| ## Training and evaluation data
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| More information needed
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|
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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: 3e-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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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| - lr_scheduler_type: linear
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| - lr_scheduler_warmup_steps: 500
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| - num_epochs: 30
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| - mixed_precision_training: Native AMP
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|
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| ### Training results
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| | Training Loss | Epoch | Step | Validation Loss | Per |
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| |:-------------:|:-------:|:-----:|:---------------:|:------:|
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| | 17.5919 | 0.7194 | 400 | 4.5477 | 0.9998 |
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| | 4.4013 | 1.4388 | 800 | 4.0848 | 0.9998 |
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| | 4.0797 | 2.1583 | 1200 | 3.6617 | 0.9998 |
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| | 3.2434 | 2.8777 | 1600 | 1.5953 | 0.4748 |
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| | 2.0985 | 3.5971 | 2000 | 0.9012 | 0.3548 |
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| | 1.6061 | 4.3165 | 2400 | 0.6137 | 0.3131 |
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| | 1.3735 | 5.0360 | 2800 | 0.4757 | 0.2970 |
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| | 1.2007 | 5.7554 | 3200 | 0.4016 | 0.2898 |
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| | 1.1208 | 6.4748 | 3600 | 0.3516 | 0.2822 |
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| | 1.0346 | 7.1942 | 4000 | 0.3281 | 0.2825 |
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| | 0.9946 | 7.9137 | 4400 | 0.3055 | 0.2807 |
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| | 0.9412 | 8.6331 | 4800 | 0.2925 | 0.2794 |
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| | 0.9012 | 9.3525 | 5200 | 0.2809 | 0.2776 |
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| | 0.8657 | 10.0719 | 5600 | 0.2775 | 0.2776 |
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| | 0.859 | 10.7914 | 6000 | 0.2680 | 0.2762 |
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| | 0.847 | 11.5108 | 6400 | 0.2662 | 0.2751 |
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| | 0.8133 | 12.2302 | 6800 | 0.2616 | 0.2753 |
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| | 0.78 | 12.9496 | 7200 | 0.2563 | 0.2744 |
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| | 0.7681 | 13.6691 | 7600 | 0.2550 | 0.2751 |
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| | 0.7648 | 14.3885 | 8000 | 0.2500 | 0.2743 |
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| | 0.7517 | 15.1079 | 8400 | 0.2485 | 0.2748 |
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| | 0.7606 | 15.8273 | 8800 | 0.2408 | 0.2731 |
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| | 0.7295 | 16.5468 | 9200 | 0.2407 | 0.2732 |
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| | 0.7193 | 17.2662 | 9600 | 0.2420 | 0.2718 |
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| | 0.7135 | 17.9856 | 10000 | 0.2376 | 0.2719 |
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| | 0.6955 | 18.7050 | 10400 | 0.2365 | 0.2726 |
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| | 0.6812 | 19.4245 | 10800 | 0.2368 | 0.2726 |
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| | 0.6962 | 20.1439 | 11200 | 0.2346 | 0.2727 |
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| | 0.6812 | 20.8633 | 11600 | 0.2360 | 0.2740 |
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| | 0.6825 | 21.5827 | 12000 | 0.2312 | 0.2729 |
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| | 0.6835 | 22.3022 | 12400 | 0.2307 | 0.2732 |
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| | 0.6704 | 23.0216 | 12800 | 0.2282 | 0.2732 |
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| | 0.6588 | 23.7410 | 13200 | 0.2299 | 0.2732 |
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| | 0.6738 | 24.4604 | 13600 | 0.2264 | 0.2719 |
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| | 0.6596 | 25.1799 | 14000 | 0.2259 | 0.2720 |
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| | 0.6559 | 25.8993 | 14400 | 0.2293 | 0.2719 |
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| | 0.6248 | 26.6187 | 14800 | 0.2266 | 0.2716 |
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| | 0.649 | 27.3381 | 15200 | 0.2283 | 0.2724 |
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| | 0.6443 | 28.0576 | 15600 | 0.2260 | 0.2725 |
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| | 0.6373 | 28.7770 | 16000 | 0.2273 | 0.2729 |
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| | 0.6233 | 29.4964 | 16400 | 0.2274 | 0.2720 |
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| ### Framework versions
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| - Transformers 4.57.6
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| - Pytorch 2.9.1+cu128
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| - Datasets 4.5.0
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| - Tokenizers 0.22.2
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|
