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---
tags:
- automatic-speech-recognition
- gary109/AI_Light_Dance
- generated_from_trainer
datasets:
- ai_light_dance
metrics:
- wer
model-index:
- name: ai-light-dance_drums_ft_pretrain_wav2vec2-base-new_onset-rbma13-2_7k
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# ai-light-dance_drums_ft_pretrain_wav2vec2-base-new_onset-rbma13-2_7k

This model is a fine-tuned version of [gary109/ai-light-dance_drums_pretrain_wav2vec2-base-new-7k](https://huggingface.co/gary109/ai-light-dance_drums_pretrain_wav2vec2-base-new-7k) on the GARY109/AI_LIGHT_DANCE - ONSET-RBMA13-2 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3330
- Wer: 1.0

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 30
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer  |
|:-------------:|:-----:|:----:|:---------------:|:----:|
| No log        | 1.0   | 1    | 68.1358         | 1.0  |
| No log        | 2.0   | 2    | 68.1358         | 1.0  |
| No log        | 3.0   | 3    | 68.1358         | 1.0  |
| No log        | 4.0   | 4    | 68.0245         | 1.0  |
| No log        | 5.0   | 5    | 67.7874         | 1.0  |
| No log        | 6.0   | 6    | 67.4535         | 1.0  |
| No log        | 7.0   | 7    | 67.0142         | 1.0  |
| No log        | 8.0   | 8    | 67.0142         | 1.0  |
| No log        | 9.0   | 9    | 66.4335         | 1.0  |
| 38.4011       | 10.0  | 10   | 65.7100         | 1.0  |
| 38.4011       | 11.0  | 11   | 64.8206         | 1.0  |
| 38.4011       | 12.0  | 12   | 63.8239         | 1.0  |
| 38.4011       | 13.0  | 13   | 62.6489         | 1.0  |
| 38.4011       | 14.0  | 14   | 61.3071         | 1.0  |
| 38.4011       | 15.0  | 15   | 59.7427         | 1.0  |
| 38.4011       | 16.0  | 16   | 58.0256         | 0.98 |
| 38.4011       | 17.0  | 17   | 56.0327         | 1.0  |
| 38.4011       | 18.0  | 18   | 53.7724         | 1.0  |
| 38.4011       | 19.0  | 19   | 51.2556         | 1.0  |
| 33.2554       | 20.0  | 20   | 48.4956         | 1.0  |
| 33.2554       | 21.0  | 21   | 45.4038         | 1.0  |
| 33.2554       | 22.0  | 22   | 41.9980         | 1.0  |
| 33.2554       | 23.0  | 23   | 41.9980         | 1.0  |
| 33.2554       | 24.0  | 24   | 38.2281         | 1.0  |
| 33.2554       | 25.0  | 25   | 34.1577         | 1.0  |
| 33.2554       | 26.0  | 26   | 29.7985         | 1.0  |
| 33.2554       | 27.0  | 27   | 25.1146         | 1.0  |
| 33.2554       | 28.0  | 28   | 20.2287         | 1.0  |
| 33.2554       | 29.0  | 29   | 15.3406         | 1.0  |
| 15.1206       | 30.0  | 30   | 10.7693         | 1.0  |
| 15.1206       | 31.0  | 31   | 6.8998          | 1.0  |
| 15.1206       | 32.0  | 32   | 4.5907          | 1.0  |
| 15.1206       | 33.0  | 33   | 3.3596          | 1.0  |
| 15.1206       | 34.0  | 34   | 2.7711          | 1.0  |
| 15.1206       | 35.0  | 35   | 2.5962          | 1.0  |
| 15.1206       | 36.0  | 36   | 2.9002          | 1.0  |
| 15.1206       | 37.0  | 37   | 3.0061          | 1.0  |
| 15.1206       | 38.0  | 38   | 2.8175          | 1.0  |
| 15.1206       | 39.0  | 39   | 2.4512          | 1.0  |
| 2.4298        | 40.0  | 40   | 2.3330          | 1.0  |
| 2.4298        | 41.0  | 41   | 2.3766          | 1.0  |
| 2.4298        | 42.0  | 42   | 2.5626          | 1.0  |
| 2.4298        | 43.0  | 43   | 2.9632          | 1.0  |
| 2.4298        | 44.0  | 44   | 3.2796          | 1.0  |
| 2.4298        | 45.0  | 45   | 3.4015          | 1.0  |
| 2.4298        | 46.0  | 46   | 3.2808          | 1.0  |
| 2.4298        | 47.0  | 47   | 3.2373          | 1.0  |
| 2.4298        | 48.0  | 48   | 3.2462          | 1.0  |
| 2.4298        | 49.0  | 49   | 3.6168          | 1.0  |
| 1.6143        | 50.0  | 50   | 3.6625          | 1.0  |
| 1.6143        | 51.0  | 51   | 3.7593          | 1.0  |
| 1.6143        | 52.0  | 52   | 3.9327          | 1.0  |
| 1.6143        | 53.0  | 53   | 3.7185          | 1.0  |
| 1.6143        | 54.0  | 54   | 3.9100          | 1.0  |
| 1.6143        | 55.0  | 55   | 4.3123          | 1.0  |
| 1.6143        | 56.0  | 56   | 4.2904          | 1.0  |
| 1.6143        | 57.0  | 57   | 3.9519          | 1.0  |
| 1.6143        | 58.0  | 58   | 3.4518          | 1.0  |
| 1.6143        | 59.0  | 59   | 3.0197          | 1.0  |
| 1.4054        | 60.0  | 60   | 2.8863          | 1.0  |
| 1.4054        | 61.0  | 61   | 2.9754          | 1.0  |
| 1.4054        | 62.0  | 62   | 3.2998          | 1.0  |
| 1.4054        | 63.0  | 63   | 3.8715          | 1.0  |
| 1.4054        | 64.0  | 64   | 4.1898          | 1.0  |
| 1.4054        | 65.0  | 65   | 4.1813          | 1.0  |
| 1.4054        | 66.0  | 66   | 3.9025          | 1.0  |
| 1.4054        | 67.0  | 67   | 3.4319          | 1.0  |
| 1.4054        | 68.0  | 68   | 3.2755          | 1.0  |
| 1.4054        | 69.0  | 69   | 3.3349          | 1.0  |
| 1.3121        | 70.0  | 70   | 3.5485          | 1.0  |
| 1.3121        | 71.0  | 71   | 3.9019          | 1.0  |
| 1.3121        | 72.0  | 72   | 4.0819          | 1.0  |
| 1.3121        | 73.0  | 73   | 3.9955          | 1.0  |
| 1.3121        | 74.0  | 74   | 3.7088          | 1.0  |
| 1.3121        | 75.0  | 75   | 3.2957          | 1.0  |
| 1.3121        | 76.0  | 76   | 3.1141          | 1.0  |
| 1.3121        | 77.0  | 77   | 3.0852          | 1.0  |
| 1.3121        | 78.0  | 78   | 3.1871          | 1.0  |
| 1.3121        | 79.0  | 79   | 3.4127          | 1.0  |
| 1.2576        | 80.0  | 80   | 3.6913          | 1.0  |
| 1.2576        | 81.0  | 81   | 3.8286          | 1.0  |
| 1.2576        | 82.0  | 82   | 3.8157          | 1.0  |
| 1.2576        | 83.0  | 83   | 3.6814          | 1.0  |
| 1.2576        | 84.0  | 84   | 3.4496          | 1.0  |
| 1.2576        | 85.0  | 85   | 3.2844          | 1.0  |
| 1.2576        | 86.0  | 86   | 3.2254          | 1.0  |
| 1.2576        | 87.0  | 87   | 3.2683          | 1.0  |
| 1.2576        | 88.0  | 88   | 3.3791          | 1.0  |
| 1.2576        | 89.0  | 89   | 3.5501          | 1.0  |
| 1.2373        | 90.0  | 90   | 3.6622          | 1.0  |
| 1.2373        | 91.0  | 91   | 3.7207          | 1.0  |
| 1.2373        | 92.0  | 92   | 3.6961          | 1.0  |
| 1.2373        | 93.0  | 93   | 3.6099          | 1.0  |
| 1.2373        | 94.0  | 94   | 3.5336          | 1.0  |
| 1.2373        | 95.0  | 95   | 3.4342          | 1.0  |
| 1.2373        | 96.0  | 96   | 3.3170          | 1.0  |
| 1.2373        | 97.0  | 97   | 3.2624          | 1.0  |
| 1.2373        | 98.0  | 98   | 3.2437          | 1.0  |
| 1.2373        | 99.0  | 99   | 3.2591          | 1.0  |
| 1.1952        | 100.0 | 100  | 3.2927          | 1.0  |


### Framework versions

- Transformers 4.25.0.dev0
- Pytorch 1.8.1+cu111
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2