Update README.md

README.md

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-license: cc-by-nc-sa-4.0
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+---
+license: cc-by-nc-sa-4.0
+---
+
+### Description
+
+This model is used to separate reverb and delay effects in vocals. In addition, it can also separate partial harmony, but it cannot completely separate them. I added random high cut after the reverberation and delay effects in the dataset, so the model's handling of high frequencies is not particularly aggressive.<br>
+You can try listening to the performance of this model [here](./examples)!
+
+### How to use the model?
+
+Try it with [ZFTurbo's Music-Source-Separation-Training](https://github.com/ZFTurbo/Music-Source-Separation-Training)
+
+### Model
+
+Configs: [config_dereverb-echo_mel_band_roformer.yaml](./config_dereverb-echo_mel_band_roformer.yaml)<br>
+Model: [dereverb-echo_mel_band_roformer_sdr_10.0169.ckpt](./dereverb-echo_mel_band_roformer_sdr_10.0169.ckpt)<br>
+Instruments: [dry, other]<br>
+Finetuned from: `model_mel_band_roformer_ep_3005_sdr_11.4360.ckpt`<br>
+Datasets: 
+- Training datasets: 270 songs from [opencpop](https://github.com/wenet-e2e/opencpop) and [GTSinger](https://github.com/GTSinger/GTSinger)
+- Validation datasets: 30 songs from my own collection
+- All random reverbs and delay effects are generated by [this python script](./scripts/create_reverb_delay.py) and sorted into the mustb18 dataset format.
+Metrics: Based on the sdr value of 30 songs for validation.
+
+```
+Instr dry sdr: 13.1507 (Std: 4.1088)
+Instr dry l1_freq: 53.7715 (Std: 13.3363)
+Instr dry si_sdr: 12.7707 (Std: 4.6134)
+Instr other sdr: 6.8830 (Std: 2.5547)
+Instr other l1_freq: 52.7358 (Std: 11.8587)
+Instr other si_sdr: 5.9448 (Std: 2.8721)
+Metric avg sdr        : 10.0169
+Metric avg l1_freq    : 53.2536
+Metric avg si_sdr     : 9.3577
+```
+
+### Training log
+
+Training logs: [train.log](./train.log)<br>
+The following image is the TensorBoard visualization training log generated by [this script](./scripts/start_tensorboard.py).
+![image](./tensorboard.png)
+
+### Thanks
+
+- Mel-Band-Roformer [[Paper](https://arxiv.org/abs/2310.01809), [Repository](https://github.com/lucidrains/BS-RoFormer)]
+- [ZFTurbo](https://github.com/ZFTurbo)'s training code [[Music-Source-Separation-Training](https://github.com/ZFTurbo/Music-Source-Separation-Training)]
+- [CN17161](https://github.com/CN17161) provided GPUs.
+- [Glucy-2](https://github.com/Glucy-2) provided technical assistance.