---
license: apache-2.0
base_model: facebook/wav2vec2-large
tags:
- generated_from_trainer
model-index:
- name: k2e-20s_asr-scr_w2v2-large_001
  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. -->

# k2e-20s_asr-scr_w2v2-large_001

This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7509
- Per: 0.1453
- Pcc: 0.6324
- Ctc Loss: 0.5111
- Mse Loss: 1.2263

## 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: 1111
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 14.3265       | 3.0   | 2235  | 4.6461          | 0.9890 | 0.6160 | 3.6176   | 1.0856   |
| 3.4446        | 6.01  | 4470  | 2.8757          | 0.3498 | 0.6516 | 1.0729   | 1.7895   |
| 1.5549        | 9.01  | 6705  | 2.0517          | 0.1846 | 0.6507 | 0.6672   | 1.3503   |
| 1.1194        | 12.02 | 8940  | 1.8625          | 0.1650 | 0.6443 | 0.5914   | 1.2388   |
| 0.9031        | 15.02 | 11175 | 1.8899          | 0.1554 | 0.6312 | 0.5473   | 1.3054   |
| 0.7614        | 18.02 | 13410 | 1.5491          | 0.1522 | 0.6307 | 0.5349   | 1.0200   |
| 0.6483        | 21.03 | 15645 | 1.8357          | 0.1481 | 0.6304 | 0.5215   | 1.2852   |
| 0.5561        | 24.03 | 17880 | 2.0576          | 0.1468 | 0.6263 | 0.5191   | 1.4774   |
| 0.5108        | 27.04 | 20115 | 1.8949          | 0.1452 | 0.6351 | 0.5090   | 1.3489   |
| 0.4778        | 30.04 | 22350 | 1.7509          | 0.1453 | 0.6324 | 0.5111   | 1.2263   |


### Framework versions

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