---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
model-index:
- name: k2e-20s_asr-scr_w2v2-base_002
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# k2e-20s_asr-scr_w2v2-base_002

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4632
- Per: 0.1621
- Pcc: 0.5775
- Ctc Loss: 0.5292
- Mse Loss: 0.9318

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 1
- seed: 2222
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2235
- training_steps: 22350
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Per    | Pcc    | Ctc Loss | Mse Loss |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 43.3938       | 1.0   | 745   | 18.4290         | 0.9890 | 0.1462 | 6.2276   | 12.2287  |
| 9.2178        | 2.0   | 1490  | 4.8023          | 0.9890 | 0.4671 | 3.8571   | 0.9719   |
| 4.753         | 3.0   | 2235  | 4.7789          | 0.9890 | 0.5587 | 3.7983   | 1.0460   |
| 4.5085        | 4.01  | 2980  | 4.4859          | 0.9890 | 0.5896 | 3.6917   | 0.8937   |
| 4.2649        | 5.01  | 3725  | 4.2852          | 0.9890 | 0.6067 | 3.6166   | 0.7981   |
| 4.0688        | 6.01  | 4470  | 4.2684          | 0.9632 | 0.6001 | 3.5490   | 0.8725   |
| 3.9012        | 7.01  | 5215  | 4.3288          | 0.9628 | 0.5973 | 3.5020   | 0.9987   |
| 3.6391        | 8.01  | 5960  | 4.2077          | 0.9430 | 0.5765 | 3.1575   | 1.2098   |
| 3.0582        | 9.01  | 6705  | 3.4214          | 0.7155 | 0.5656 | 2.3835   | 1.1480   |
| 2.3307        | 10.01 | 7450  | 2.4659          | 0.4524 | 0.5672 | 1.6378   | 0.8917   |
| 1.7509        | 11.01 | 8195  | 2.3288          | 0.3189 | 0.5824 | 1.1749   | 1.1589   |
| 1.3679        | 12.02 | 8940  | 2.0410          | 0.2541 | 0.5669 | 0.9275   | 1.0986   |
| 1.1463        | 13.02 | 9685  | 1.8387          | 0.2238 | 0.5714 | 0.8029   | 1.0158   |
| 1.013         | 14.02 | 10430 | 1.6558          | 0.2068 | 0.5635 | 0.7253   | 0.9141   |
| 0.912         | 15.02 | 11175 | 1.6381          | 0.1992 | 0.5530 | 0.6788   | 0.9381   |
| 0.8321        | 16.02 | 11920 | 1.8336          | 0.1908 | 0.5660 | 0.6407   | 1.1459   |
| 0.7676        | 17.02 | 12665 | 1.6002          | 0.1819 | 0.5851 | 0.6197   | 0.9574   |
| 0.7186        | 18.02 | 13410 | 1.6110          | 0.1807 | 0.5562 | 0.5981   | 0.9870   |
| 0.6707        | 19.03 | 14155 | 1.6138          | 0.1748 | 0.5735 | 0.5827   | 1.0041   |
| 0.6362        | 20.03 | 14900 | 1.5090          | 0.1729 | 0.5706 | 0.5688   | 0.9264   |
| 0.6016        | 21.03 | 15645 | 1.5540          | 0.1698 | 0.5742 | 0.5619   | 0.9732   |
| 0.5724        | 22.03 | 16390 | 1.5076          | 0.1686 | 0.5846 | 0.5517   | 0.9435   |
| 0.5434        | 23.03 | 17135 | 1.4442          | 0.1676 | 0.5753 | 0.5443   | 0.8970   |
| 0.5272        | 24.03 | 17880 | 1.4617          | 0.1656 | 0.5699 | 0.5409   | 0.9165   |
| 0.5119        | 25.03 | 18625 | 1.4886          | 0.1642 | 0.5654 | 0.5400   | 0.9414   |
| 0.4963        | 26.03 | 19370 | 1.4959          | 0.1644 | 0.5751 | 0.5342   | 0.9534   |
| 0.4882        | 27.04 | 20115 | 1.4686          | 0.1634 | 0.5711 | 0.5320   | 0.9329   |
| 0.4697        | 28.04 | 20860 | 1.4663          | 0.1627 | 0.5730 | 0.5302   | 0.9330   |
| 0.4604        | 29.04 | 21605 | 1.4417          | 0.1623 | 0.5782 | 0.5293   | 0.9134   |
| 0.4536        | 30.04 | 22350 | 1.4632          | 0.1621 | 0.5775 | 0.5292   | 0.9318   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.2