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@ -35,6 +35,9 @@ Also, users can use tensorboard to observe these training information by the fol
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```sh
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tensorboard --logdir ${exp_dir}/exp/${model_dir}/tensorboard/train
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```
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Here is an example of loss:
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<img src="images/loss.png" width="200"/>
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The inference results are saved in `${exp_dir}/exp/${model_dir}/decode_asr_*/$dset`. The main two files are `text.cer` and `text.cer.txt`. `text.cer` saves the comparison between the recognized text and the reference text, like follows:
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```text
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@ -177,7 +180,7 @@ The configuration of the model is set in the config file `conf/train_*.yaml`. Sp
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encoder: conformer
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encoder_conf:
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output_size: 256 # dimension of attention
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attention_heads: 4 # number of heads in multi-head attention
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attention_heads: 4 # the number of heads in multi-head attention
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linear_units: 2048 # the number of units of position-wise feed forward
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num_blocks: 12 # the number of encoder blocks
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dropout_rate: 0.1
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docs/academic_recipe/images/loss.png
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docs/academic_recipe/images/loss.png
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