---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
model-index:
- name: cmb-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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# cmb-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: 0.1978
- Per: 0.1287
- Pcc: 0.6493
- Ctc Loss: 0.4014
- Mse Loss: 0.9499

## 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: 8928
- training_steps: 89280
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Per    | Pcc    | Ctc Loss | Mse Loss |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 11.3245       | 3.0   | 8928  | 4.4416          | 0.9956 | 0.6159 | 3.7640   | 0.8975   |
| 2.9636        | 6.0   | 17856 | 1.4930          | 0.1745 | 0.6638 | 0.6280   | 0.8352   |
| 1.0327        | 9.0   | 26784 | 1.3313          | 0.1461 | 0.6666 | 0.4797   | 0.8799   |
| 0.5448        | 12.0  | 35712 | 1.2880          | 0.1394 | 0.6530 | 0.4501   | 0.9425   |
| 0.1232        | 15.0  | 44640 | 1.0484          | 0.1354 | 0.6481 | 0.4289   | 0.8871   |
| -0.3248       | 18.0  | 53568 | 1.3777          | 0.1330 | 0.6373 | 0.4163   | 1.1622   |
| -0.7634       | 21.0  | 62496 | 1.0371          | 0.1312 | 0.6499 | 0.4094   | 1.0824   |
| -1.2089       | 24.0  | 71424 | 0.4166          | 0.1298 | 0.6454 | 0.4060   | 0.9053   |
| -1.613        | 27.0  | 80352 | 0.2751          | 0.1290 | 0.6473 | 0.4021   | 0.9426   |
| -1.8704       | 30.0  | 89280 | 0.1978          | 0.1287 | 0.6493 | 0.4014   | 0.9499   |


### Framework versions

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