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Kyro-2023
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wav2vec2-large-mms-1b-zh-CN

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +245 -0
  2. adapter.zh-CN.safetensors +3 -0
  3. pytorch_model.bin +1 -1
README.md ADDED
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+ ---
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+ license: cc-by-nc-4.0
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+ base_model: facebook/mms-1b-all
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - common_voice_6_1
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+ model-index:
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+ - name: wav2vec2-large-mms-1b-zh-CN
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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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+ # wav2vec2-large-mms-1b-zh-CN
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+
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+ This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_6_1 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9552
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+ - Cer: 0.2071
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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: 0.001
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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: 100
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+ - num_epochs: 8
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Cer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 42.0738 | 0.04 | 100 | 2.9914 | 0.4865 |
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+ | 2.534 | 0.09 | 200 | 2.0714 | 0.3981 |
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+ | 2.0311 | 0.13 | 300 | 1.9086 | 0.3844 |
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+ | 1.9237 | 0.17 | 400 | 1.7770 | 0.3650 |
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+ | 1.865 | 0.22 | 500 | 1.6745 | 0.3579 |
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+ | 1.8275 | 0.26 | 600 | 1.6277 | 0.3414 |
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+ | 1.8094 | 0.3 | 700 | 1.6812 | 0.3639 |
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+ | 1.7503 | 0.35 | 800 | 1.6279 | 0.3427 |
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+ | 1.7448 | 0.39 | 900 | 1.5611 | 0.3376 |
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+ | 1.7459 | 0.43 | 1000 | 1.5413 | 0.3323 |
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+ | 1.7191 | 0.47 | 1100 | 1.5259 | 0.3280 |
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+ | 1.6317 | 0.52 | 1200 | 1.5102 | 0.3242 |
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+ | 1.6881 | 0.56 | 1300 | 1.4851 | 0.3212 |
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+ | 1.6401 | 0.6 | 1400 | 1.4589 | 0.3097 |
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+ | 1.5909 | 0.65 | 1500 | 1.4985 | 0.3186 |
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+ | 1.618 | 0.69 | 1600 | 1.4415 | 0.3122 |
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+ | 1.6842 | 0.73 | 1700 | 1.4596 | 0.3161 |
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+ | 1.5413 | 0.78 | 1800 | 1.4275 | 0.3003 |
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+ | 1.6461 | 0.82 | 1900 | 1.4214 | 0.3073 |
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+ | 1.5536 | 0.86 | 2000 | 1.3924 | 0.3003 |
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+ | 1.545 | 0.91 | 2100 | 1.3727 | 0.2907 |
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+ | 1.6354 | 0.95 | 2200 | 1.4157 | 0.3088 |
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+ | 1.4913 | 0.99 | 2300 | 1.4012 | 0.3042 |
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+ | 1.2739 | 1.04 | 2400 | 1.3079 | 0.2855 |
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+ | 1.2292 | 1.08 | 2500 | 1.3085 | 0.2832 |
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+ | 1.2424 | 1.12 | 2600 | 1.3273 | 0.2879 |
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+ | 1.2181 | 1.16 | 2700 | 1.3241 | 0.2864 |
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+ | 1.2101 | 1.21 | 2800 | 1.2526 | 0.2780 |
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+ | 1.26 | 1.25 | 2900 | 1.2949 | 0.2815 |
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+ | 1.2154 | 1.29 | 3000 | 1.2932 | 0.2787 |
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+ | 1.2446 | 1.34 | 3100 | 1.2774 | 0.2792 |
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+ | 1.1975 | 1.38 | 3200 | 1.2641 | 0.2751 |
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+ | 1.2048 | 1.42 | 3300 | 1.2645 | 0.2773 |
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+ | 1.1858 | 1.47 | 3400 | 1.2616 | 0.2741 |
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+ | 1.202 | 1.51 | 3500 | 1.2572 | 0.2725 |
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+ | 1.1802 | 1.55 | 3600 | 1.2554 | 0.2723 |
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+ | 1.1912 | 1.6 | 3700 | 1.2703 | 0.2657 |
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+ | 1.213 | 1.64 | 3800 | 1.2491 | 0.2743 |
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+ | 1.1949 | 1.68 | 3900 | 1.2497 | 0.2734 |
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+ | 1.1813 | 1.73 | 4000 | 1.2367 | 0.2709 |
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+ | 1.1935 | 1.77 | 4100 | 1.2174 | 0.2677 |
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+ | 1.1842 | 1.81 | 4200 | 1.2307 | 0.2660 |
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+ | 1.215 | 1.86 | 4300 | 1.2275 | 0.2696 |
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+ | 1.2102 | 1.9 | 4400 | 1.1964 | 0.2595 |
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+ | 1.2206 | 1.94 | 4500 | 1.2046 | 0.2574 |
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+ | 1.2292 | 1.98 | 4600 | 1.1900 | 0.2595 |
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+ | 1.034 | 2.03 | 4700 | 1.1849 | 0.2547 |
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+ | 0.8787 | 2.07 | 4800 | 1.1889 | 0.2558 |
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+ | 0.9124 | 2.11 | 4900 | 1.1809 | 0.2590 |
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+ | 0.9027 | 2.16 | 5000 | 1.1927 | 0.2608 |
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+ | 0.9158 | 2.2 | 5100 | 1.1860 | 0.2556 |
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+ | 0.8683 | 2.24 | 5200 | 1.1660 | 0.2522 |
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+ | 0.8932 | 2.29 | 5300 | 1.1477 | 0.2533 |
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+ | 0.9332 | 2.33 | 5400 | 1.1702 | 0.2543 |
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+ | 0.9427 | 2.37 | 5500 | 1.1653 | 0.2523 |
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+ | 0.9085 | 2.42 | 5600 | 1.1739 | 0.2539 |
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+ | 0.9238 | 2.46 | 5700 | 1.2005 | 0.2589 |
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+ | 0.9319 | 2.5 | 5800 | 1.1877 | 0.2567 |
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+ | 0.9414 | 2.55 | 5900 | 1.1730 | 0.2505 |
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+ | 0.9428 | 2.59 | 6000 | 1.1721 | 0.2576 |
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+ | 0.942 | 2.63 | 6100 | 1.1793 | 0.2547 |
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+ | 0.9273 | 2.67 | 6200 | 1.1787 | 0.2570 |
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+ | 0.9963 | 2.72 | 6300 | 1.1570 | 0.2540 |
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+ | 0.9519 | 2.76 | 6400 | 1.1738 | 0.2563 |
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+ | 0.962 | 2.8 | 6500 | 1.1929 | 0.2628 |
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+ | 0.9765 | 2.85 | 6600 | 1.1531 | 0.2527 |
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+ | 0.9186 | 2.98 | 6900 | 1.1402 | 0.2500 |
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+ | 0.8681 | 3.02 | 7000 | 1.1520 | 0.2516 |
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+ | 0.7738 | 3.06 | 7100 | 1.1404 | 0.2527 |
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+ | 0.7605 | 3.11 | 7200 | 1.1535 | 0.2514 |
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+ | 0.7254 | 3.15 | 7300 | 1.1679 | 0.2490 |
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+ | 0.7422 | 3.19 | 7400 | 1.1536 | 0.2502 |
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+ | 0.823 | 3.24 | 7500 | 1.1516 | 0.2477 |
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+ | 0.7909 | 3.28 | 7600 | 1.1442 | 0.2459 |
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+ | 0.7748 | 3.32 | 7700 | 1.1522 | 0.2493 |
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+ | 0.7957 | 3.36 | 7800 | 1.1383 | 0.2470 |
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+ | 0.8093 | 3.45 | 8000 | 1.1426 | 0.2467 |
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+ | 0.7891 | 3.54 | 8200 | 1.1552 | 0.2480 |
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+ | 0.8246 | 3.58 | 8300 | 1.1555 | 0.2475 |
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+ | 0.6358 | 4.31 | 10000 | 1.0722 | 0.2313 |
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+ | 0.6531 | 4.36 | 10100 | 1.0796 | 0.2326 |
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+ | 0.6383 | 4.4 | 10200 | 1.0736 | 0.2322 |
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+ | 0.5392 | 5.44 | 12600 | 1.0469 | 0.2253 |
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+ | 0.5867 | 5.48 | 12700 | 1.0373 | 0.2264 |
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+ | 0.4256 | 7.03 | 16300 | 0.9771 | 0.2131 |
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+ | 0.4133 | 7.08 | 16400 | 0.9803 | 0.2125 |
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+ | 0.4051 | 7.12 | 16500 | 0.9778 | 0.2116 |
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+ | 0.4274 | 7.16 | 16600 | 0.9809 | 0.2116 |
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+ | 0.4307 | 7.2 | 16700 | 0.9720 | 0.2109 |
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+ | 0.4223 | 7.25 | 16800 | 0.9730 | 0.2109 |
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+ | 0.4246 | 7.29 | 16900 | 0.9710 | 0.2100 |
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+ | 0.4478 | 7.33 | 17000 | 0.9670 | 0.2101 |
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+ | 0.4016 | 7.38 | 17100 | 0.9664 | 0.2096 |
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+ | 0.4289 | 7.42 | 17200 | 0.9667 | 0.2093 |
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+ | 0.4107 | 7.46 | 17300 | 0.9661 | 0.2096 |
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+ | 0.4643 | 7.51 | 17400 | 0.9665 | 0.2106 |
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+ | 0.433 | 7.55 | 17500 | 0.9673 | 0.2097 |
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+ | 0.4239 | 7.59 | 17600 | 0.9639 | 0.2096 |
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+ | 0.4144 | 7.64 | 17700 | 0.9635 | 0.2091 |
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+ | 0.428 | 7.68 | 17800 | 0.9604 | 0.2094 |
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+ | 0.4312 | 7.72 | 17900 | 0.9585 | 0.2099 |
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+ | 0.4164 | 7.77 | 18000 | 0.9599 | 0.2093 |
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+ | 0.4308 | 7.81 | 18100 | 0.9587 | 0.2080 |
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+ | 0.4177 | 7.85 | 18200 | 0.9575 | 0.2084 |
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+ | 0.4509 | 7.89 | 18300 | 0.9567 | 0.2082 |
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+ | 0.4244 | 7.94 | 18400 | 0.9558 | 0.2072 |
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+ | 0.4246 | 7.98 | 18500 | 0.9552 | 0.2071 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.0.dev0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
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