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NX2411
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wav2vec2-large-xlsr-korean-demo-test2

Automatic Speech Recognition
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PyTorch
TensorBoard
wav2vec2
Generated from Trainer
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  license: apache-2.0
 
 
 
 
 
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  license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: wav2vec2-large-xlsr-korean-demo-test2
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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-xlsr-korean-demo-test2
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9948
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+ - Wer: 0.5865
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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: 15
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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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+ | 29.8545 | 0.3 | 400 | 5.3860 | 1.0 |
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+ | 4.9621 | 0.59 | 800 | 5.4067 | 1.0 |
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+ | 4.9254 | 0.89 | 1200 | 5.1930 | 1.0 |
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+ | 4.8425 | 1.19 | 1600 | 5.0176 | 1.0 |
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+ | 4.7955 | 1.49 | 2000 | 5.0994 | 1.0 |
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+ | 4.7091 | 1.78 | 2400 | 4.6204 | 1.0 |
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+ | 4.4177 | 2.08 | 2800 | 3.8672 | 1.0 |
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+ | 3.5708 | 2.38 | 3200 | 2.8938 | 0.9548 |
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+ | 2.9828 | 2.67 | 3600 | 2.4027 | 0.9100 |
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+ | 2.6781 | 2.97 | 4000 | 2.0710 | 0.8728 |
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+ | 2.3347 | 3.27 | 4400 | 1.8604 | 0.8474 |
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+ | 2.2081 | 3.57 | 4800 | 1.7831 | 0.8116 |
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+ | 2.1184 | 3.86 | 5200 | 1.6272 | 0.8012 |
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+ | 1.9834 | 4.16 | 5600 | 1.5311 | 0.8007 |
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+ | 1.8402 | 4.46 | 6000 | 1.4352 | 0.7659 |
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+ | 1.7859 | 4.75 | 6400 | 1.3503 | 0.7485 |
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+ | 1.7374 | 5.05 | 6800 | 1.3561 | 0.7674 |
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+ | 1.5966 | 5.35 | 7200 | 1.3319 | 0.7222 |
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+ | 1.5716 | 5.65 | 7600 | 1.2539 | 0.7112 |
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+ | 1.579 | 5.94 | 8000 | 1.2456 | 0.7028 |
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+ | 1.4429 | 6.24 | 8400 | 1.2081 | 0.6884 |
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+ | 1.4176 | 6.54 | 8800 | 1.1681 | 0.6914 |
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+ | 1.403 | 6.84 | 9200 | 1.1583 | 0.6874 |
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+ | 1.3417 | 7.13 | 9600 | 1.1235 | 0.6590 |
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+ | 1.267 | 7.43 | 10000 | 1.1538 | 0.6720 |
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+ | 1.268 | 7.73 | 10400 | 1.0878 | 0.6556 |
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+ | 1.2245 | 8.02 | 10800 | 1.0759 | 0.6347 |
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+ | 1.1437 | 8.32 | 11200 | 1.0815 | 0.6412 |
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+ | 1.1386 | 8.62 | 11600 | 1.1007 | 0.6352 |
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+ | 1.1045 | 8.92 | 12000 | 1.0574 | 0.6521 |
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+ | 1.0533 | 9.21 | 12400 | 1.0772 | 0.6332 |
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+ | 1.0274 | 9.51 | 12800 | 1.0622 | 0.6267 |
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+ | 1.0398 | 9.81 | 13200 | 1.0380 | 0.6322 |
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+ | 0.9869 | 10.1 | 13600 | 1.0654 | 0.6267 |
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+ | 0.9309 | 10.4 | 14000 | 1.0505 | 0.6153 |
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+ | 0.9231 | 10.7 | 14400 | 1.0300 | 0.6128 |
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+ | 0.9324 | 11.0 | 14800 | 0.9777 | 0.6098 |
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+ | 0.8467 | 11.29 | 15200 | 1.0123 | 0.6133 |
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+ | 0.8471 | 11.59 | 15600 | 1.0086 | 0.6014 |
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+ | 0.8601 | 11.89 | 16000 | 1.0051 | 0.6004 |
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+ | 0.8111 | 12.18 | 16400 | 1.0242 | 0.5994 |
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+ | 0.7525 | 12.48 | 16800 | 1.0015 | 0.5875 |
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+ | 0.7697 | 12.78 | 17200 | 0.9987 | 0.5954 |
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+ | 0.7585 | 13.08 | 17600 | 1.0040 | 0.5949 |
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+ | 0.7163 | 13.37 | 18000 | 0.9584 | 0.5895 |
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+ | 0.7041 | 13.67 | 18400 | 0.9795 | 0.5885 |
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+ | 0.7115 | 13.97 | 18800 | 0.9726 | 0.5840 |
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+ | 0.6907 | 14.26 | 19200 | 0.9809 | 0.5855 |
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+ | 0.6847 | 14.56 | 19600 | 0.9979 | 0.5870 |
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+ | 0.6641 | 14.86 | 20000 | 0.9948 | 0.5865 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.21.1
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+ - Pytorch 1.12.1+cu113
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+ - Datasets 2.4.0
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+ - Tokenizers 0.12.1