---
license: apache-2.0
base_model: facebook/wav2vec2-large-lv60
tags:
- generated_from_trainer
model-index:
- name: k2e-20s_asr-scr_w2v2-large-lv60_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-lv60_001

This model is a fine-tuned version of [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9960
- Per: 0.9491
- Pcc: 0.4581
- Ctc Loss: 2.9538
- Mse Loss: 1.3478

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

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Per    | Pcc    | Ctc Loss | Mse Loss |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 30.007        | 3.0   | 2235  | 4.9713          | 0.9890 | 0.4691 | 3.8731   | 1.1616   |
| 4.5436        | 6.01  | 4470  | 4.8907          | 0.9890 | 0.4458 | 3.7192   | 1.3424   |
| 4.1973        | 9.01  | 6705  | 4.7504          | 0.9890 | 0.4791 | 3.6454   | 1.3436   |
| 3.9659        | 12.02 | 8940  | 4.9631          | 0.9627 | 0.3953 | 3.5684   | 1.6631   |
| 3.7945        | 15.02 | 11175 | 4.6238          | 0.9627 | 0.3228 | 3.5522   | 1.3937   |
| 3.657         | 18.02 | 13410 | 4.8315          | 0.9627 | 0.3795 | 3.4947   | 1.6564   |
| 3.4943        | 21.03 | 15645 | 4.5083          | 0.9626 | 0.4295 | 3.3623   | 1.4824   |
| 3.3082        | 24.03 | 17880 | 4.1212          | 0.9625 | 0.4469 | 3.1651   | 1.2958   |
| 3.1432        | 27.04 | 20115 | 4.1271          | 0.9586 | 0.4566 | 3.0120   | 1.4192   |
| 3.0438        | 30.04 | 22350 | 3.9960          | 0.9491 | 0.4581 | 2.9538   | 1.3478   |


### Framework versions

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