---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
model-index:
- name: k2e-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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# k2e-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: 1.6527
- Per: 0.1654
- Pcc: 0.5394
- Ctc Loss: 0.5408
- Mse Loss: 1.0678

## 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: 2235
- training_steps: 22350
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Per    | Pcc    | Ctc Loss | Mse Loss |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 19.3751       | 3.0   | 2235  | 4.7433          | 0.9890 | 0.5024 | 3.8252   | 0.9851   |
| 4.4284        | 6.01  | 4470  | 4.4301          | 0.9890 | 0.5830 | 3.7430   | 0.8578   |
| 3.9191        | 9.01  | 6705  | 4.2301          | 0.9630 | 0.5507 | 3.4950   | 0.9591   |
| 2.958         | 12.02 | 8940  | 2.8191          | 0.5448 | 0.5582 | 1.7723   | 1.1213   |
| 1.4445        | 15.02 | 11175 | 2.0895          | 0.2288 | 0.5320 | 0.8429   | 1.2066   |
| 0.9277        | 18.02 | 13410 | 1.7961          | 0.1901 | 0.5394 | 0.6581   | 1.0903   |
| 0.7339        | 21.03 | 15645 | 1.8166          | 0.1779 | 0.5342 | 0.5943   | 1.1613   |
| 0.6237        | 24.03 | 17880 | 1.7384          | 0.1702 | 0.5290 | 0.5628   | 1.1210   |
| 0.5593        | 27.04 | 20115 | 1.6879          | 0.1667 | 0.5392 | 0.5459   | 1.0930   |
| 0.5212        | 30.04 | 22350 | 1.6527          | 0.1654 | 0.5394 | 0.5408   | 1.0678   |


### Framework versions

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