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Automatic Speech Recognition
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wav2vec2
Generated from Trainer
Eval Results (legacy)
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End of training

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  1. README.md +115 -0
  2. runs/Jun10_22-24-02_989d23a822eb/events.out.tfevents.1718058315.989d23a822eb.2401.0 +2 -2
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
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - audiofolder
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: results
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: audiofolder
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+ type: audiofolder
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+ config: default
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+ split: test
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+ args: default
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.47755303404045385
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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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+ # results
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+
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+ This model is a fine-tuned version of [facebook/mms-1b](https://huggingface.co/facebook/mms-1b) on the audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.0362
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+ - Wer: 0.4776
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+ - Cer: 0.2418
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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: 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: 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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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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+ |:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
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+ | 3.0435 | 0.8247 | 40 | 2.9730 | 1.0 | 1.0 |
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+ | 1.7257 | 1.6495 | 80 | 1.5913 | 0.8155 | 0.3725 |
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+ | 1.2559 | 2.4742 | 120 | 1.3284 | 0.6922 | 0.3104 |
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+ | 1.0506 | 3.2990 | 160 | 1.2850 | 0.6374 | 0.2965 |
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+ | 0.9286 | 4.1237 | 200 | 1.2555 | 0.5530 | 0.2589 |
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+ | 0.9036 | 4.9485 | 240 | 1.2799 | 0.5969 | 0.2754 |
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+ | 0.8737 | 5.7732 | 280 | 1.3403 | 0.5826 | 0.2751 |
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+ | 0.7498 | 6.5979 | 320 | 1.2827 | 0.5590 | 0.2747 |
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+ | 0.772 | 7.4227 | 360 | 1.3825 | 0.5792 | 0.2854 |
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+ | 0.6421 | 8.2474 | 400 | 1.5132 | 0.6167 | 0.2903 |
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+ | 0.6352 | 9.0722 | 440 | 1.4360 | 0.5654 | 0.2712 |
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+ | 0.6812 | 9.8969 | 480 | 1.3643 | 0.5816 | 0.2905 |
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+ | 0.6641 | 10.7216 | 520 | 1.5933 | 0.6014 | 0.2834 |
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+ | 0.5466 | 11.5464 | 560 | 1.4724 | 0.5565 | 0.2766 |
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+ | 0.5291 | 12.3711 | 600 | 1.5755 | 0.5545 | 0.2685 |
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+ | 0.41 | 13.1959 | 640 | 1.5586 | 0.5560 | 0.2744 |
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+ | 0.3679 | 14.0206 | 680 | 1.5788 | 0.5644 | 0.2746 |
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+ | 0.2847 | 14.8454 | 720 | 1.6370 | 0.5407 | 0.2655 |
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+ | 0.314 | 15.6701 | 760 | 1.7064 | 0.5456 | 0.2693 |
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+ | 0.231 | 16.4948 | 800 | 1.5744 | 0.5466 | 0.2705 |
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+ | 0.2123 | 17.3196 | 840 | 1.7739 | 0.5358 | 0.2661 |
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+ | 0.1241 | 18.1443 | 880 | 1.8826 | 0.5116 | 0.2536 |
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+ | 0.1361 | 18.9691 | 920 | 1.8170 | 0.5264 | 0.2639 |
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+ | 0.1363 | 19.7938 | 960 | 1.7761 | 0.5131 | 0.2550 |
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+ | 0.1061 | 20.6186 | 1000 | 1.9435 | 0.5032 | 0.2531 |
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+ | 0.077 | 21.4433 | 1040 | 1.9086 | 0.5067 | 0.2554 |
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+ | 0.086 | 22.2680 | 1080 | 1.8842 | 0.5150 | 0.2560 |
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+ | 0.0791 | 23.0928 | 1120 | 1.9835 | 0.5027 | 0.2504 |
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+ | 0.0925 | 23.9175 | 1160 | 1.9887 | 0.4983 | 0.2493 |
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+ | 0.1021 | 24.7423 | 1200 | 1.9644 | 0.5002 | 0.2465 |
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+ | 0.0623 | 25.5670 | 1240 | 2.0038 | 0.4889 | 0.2456 |
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+ | 0.0537 | 26.3918 | 1280 | 1.9788 | 0.4879 | 0.2455 |
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+ | 0.0428 | 27.2165 | 1320 | 1.9889 | 0.4780 | 0.2433 |
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+ | 0.1203 | 28.0412 | 1360 | 2.0245 | 0.4805 | 0.2459 |
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+ | 0.0365 | 28.8660 | 1400 | 2.0261 | 0.4810 | 0.2427 |
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+ | 0.0247 | 29.6907 | 1440 | 2.0362 | 0.4776 | 0.2418 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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