---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
model-index:
- name: pic-20s_asr-scr_w2v2-base_001
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# pic-20s_asr-scr_w2v2-base_001

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: 1.4443
- Per: 0.1499
- Pcc: 0.6371
- Ctc Loss: 0.5406
- Mse Loss: 0.8841

## 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: 2247
- training_steps: 22470
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Per    | Pcc    | Ctc Loss | Mse Loss |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 16.6841       | 3.0   | 2247  | 4.7118          | 0.9979 | 0.6160 | 3.7745   | 1.0013   |
| 4.2857        | 6.0   | 4494  | 4.2485          | 0.9979 | 0.6999 | 3.7428   | 0.6844   |
| 3.9118        | 9.0   | 6741  | 4.2032          | 0.9979 | 0.6863 | 3.7209   | 0.7501   |
| 3.5336        | 12.0  | 8988  | 3.8740          | 0.9976 | 0.6645 | 3.1591   | 0.9697   |
| 2.1131        | 15.0  | 11235 | 2.0043          | 0.2726 | 0.6564 | 1.1426   | 0.8936   |
| 0.9858        | 18.0  | 13482 | 1.6048          | 0.1817 | 0.6377 | 0.7083   | 0.8783   |
| 0.7106        | 21.0  | 15729 | 1.5797          | 0.1625 | 0.6447 | 0.6061   | 0.9394   |
| 0.5928        | 24.0  | 17976 | 1.4856          | 0.1552 | 0.6392 | 0.5624   | 0.8977   |
| 0.525         | 27.0  | 20223 | 1.4673          | 0.1515 | 0.6343 | 0.5471   | 0.8972   |
| 0.4862        | 30.0  | 22470 | 1.4443          | 0.1499 | 0.6371 | 0.5406   | 0.8841   |


### Framework versions

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