---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
model-index:
- name: saq-20s_asr-scr_w2v2-base_003
  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_003

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: 1.4770
- Per: 0.1582
- Pcc: 0.6742
- Ctc Loss: 0.5610
- Mse Loss: 0.8995

## 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: 3333
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 16.8423       | 3.0   | 2226  | 4.5928          | 0.9983 | 0.6376 | 3.7671   | 0.8900   |
| 4.329         | 6.0   | 4452  | 4.5763          | 0.9983 | 0.6939 | 3.7500   | 0.9944   |
| 3.9518        | 9.0   | 6678  | 4.3570          | 0.9983 | 0.6962 | 3.7043   | 0.9024   |
| 3.4509        | 12.0  | 8904  | 3.2020          | 0.8036 | 0.6831 | 2.6097   | 0.7935   |
| 1.6554        | 15.0  | 11130 | 1.7792          | 0.2361 | 0.6712 | 0.9476   | 0.8436   |
| 0.9205        | 18.0  | 13356 | 1.6586          | 0.1900 | 0.6858 | 0.7026   | 0.9314   |
| 0.7081        | 21.0  | 15582 | 1.5955          | 0.1721 | 0.6716 | 0.6236   | 0.9429   |
| 0.5965        | 24.0  | 17808 | 1.5239          | 0.1634 | 0.6784 | 0.5880   | 0.9140   |
| 0.5351        | 27.0  | 20034 | 1.4992          | 0.1595 | 0.6782 | 0.5682   | 0.9115   |
| 0.5012        | 30.0  | 22260 | 1.4770          | 0.1582 | 0.6742 | 0.5610   | 0.8995   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.15.2