---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
model-index:
- name: saq-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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# saq-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: 1.5036
- Per: 0.1541
- Pcc: 0.6677
- Ctc Loss: 0.5422
- Mse Loss: 0.9427

## 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: 2226
- training_steps: 22260
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Per    | Pcc    | Ctc Loss | Mse Loss |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 16.9349       | 3.0   | 2226  | 4.6257          | 0.9983 | 0.6397 | 3.7753   | 0.9152   |
| 4.358         | 6.0   | 4452  | 4.3728          | 0.9983 | 0.6743 | 3.7449   | 0.7973   |
| 3.976         | 9.0   | 6678  | 4.2399          | 0.9983 | 0.6928 | 3.6699   | 0.8195   |
| 2.9839        | 12.0  | 8904  | 2.3433          | 0.3730 | 0.6740 | 1.5100   | 0.8973   |
| 1.2641        | 15.0  | 11130 | 1.7650          | 0.2095 | 0.6732 | 0.7985   | 0.9498   |
| 0.8466        | 18.0  | 13356 | 1.5664          | 0.1818 | 0.6642 | 0.6611   | 0.8872   |
| 0.6752        | 21.0  | 15582 | 1.5958          | 0.1708 | 0.6690 | 0.6012   | 0.9664   |
| 0.5802        | 24.0  | 17808 | 1.7719          | 0.1651 | 0.6737 | 0.5668   | 1.1474   |
| 0.5266        | 27.0  | 20034 | 1.6479          | 0.1577 | 0.6707 | 0.5482   | 1.0587   |
| 0.4851        | 30.0  | 22260 | 1.5036          | 0.1541 | 0.6677 | 0.5422   | 0.9427   |


### Framework versions

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