---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
model-index:
- name: pic-20s_asr-scr_w2v2-base_004
  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. -->

# pic-20s_asr-scr_w2v2-base_004

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: 1.4351
- Per: 0.1529
- Pcc: 0.6741
- Ctc Loss: 0.5362
- Mse Loss: 0.8881

## 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: 1234
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 17.1513       | 3.0   | 2247  | 4.7158          | 0.9979 | 0.6302 | 3.7674   | 1.0133   |
| 4.2201        | 6.0   | 4494  | 4.2724          | 0.9979 | 0.7096 | 3.7172   | 0.7331   |
| 3.7967        | 9.0   | 6741  | 4.3058          | 0.9975 | 0.6875 | 3.6713   | 0.8900   |
| 3.0022        | 12.0  | 8988  | 2.4439          | 0.5310 | 0.6794 | 1.8297   | 0.7356   |
| 1.3508        | 15.0  | 11235 | 1.8496          | 0.2221 | 0.6786 | 0.8430   | 0.9894   |
| 0.825         | 18.0  | 13482 | 1.5793          | 0.1815 | 0.6751 | 0.6577   | 0.8999   |
| 0.6436        | 21.0  | 15729 | 1.7474          | 0.1690 | 0.6748 | 0.5867   | 1.1030   |
| 0.5476        | 24.0  | 17976 | 1.4824          | 0.1589 | 0.6730 | 0.5570   | 0.9069   |
| 0.4889        | 27.0  | 20223 | 1.3293          | 0.1544 | 0.6701 | 0.5413   | 0.7952   |
| 0.4593        | 30.0  | 22470 | 1.4351          | 0.1529 | 0.6741 | 0.5362   | 0.8881   |


### Framework versions

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