---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
model-index:
- name: cmb-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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# cmb-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: 0.2887
- Per: 0.1279
- Pcc: 0.6501
- Ctc Loss: 0.3968
- Mse Loss: 1.0164

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

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Per    | Pcc    | Ctc Loss | Mse Loss |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 11.516        | 3.0   | 8928  | 4.4204          | 0.9956 | 0.6302 | 3.7718   | 0.8695   |
| 2.6821        | 6.0   | 17856 | 1.4363          | 0.1800 | 0.6754 | 0.6151   | 0.8033   |
| 1.0205        | 9.0   | 26784 | 1.4608          | 0.1457 | 0.6734 | 0.4819   | 0.9911   |
| 0.5238        | 12.0  | 35712 | 1.1546          | 0.1375 | 0.6624 | 0.4382   | 0.8751   |
| 0.0849        | 15.0  | 44640 | 1.2248          | 0.1338 | 0.6576 | 0.4181   | 1.0163   |
| -0.3644       | 18.0  | 53568 | 1.4907          | 0.1314 | 0.6513 | 0.4077   | 1.2464   |
| -0.8166       | 21.0  | 62496 | 0.5897          | 0.1302 | 0.6518 | 0.4054   | 0.8912   |
| -1.2642       | 24.0  | 71424 | 0.5638          | 0.1286 | 0.6511 | 0.3985   | 0.9995   |
| -1.6765       | 27.0  | 80352 | 0.4494          | 0.1282 | 0.6490 | 0.3980   | 1.0442   |
| -1.9395       | 30.0  | 89280 | 0.2887          | 0.1279 | 0.6501 | 0.3968   | 1.0164   |


### Framework versions

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