transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer base_model:facebook/wav2vec2-xls-r-300m license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: ft_0122_korean
  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. -->

# ft_0122_korean

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3680
- Cer: 0.3009

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 46.2918       | 0.08  | 100  | 50.8931         | 1.0    |
| 15.0805       | 0.16  | 200  | 8.0154          | 1.0    |
| 5.0807        | 0.24  | 300  | 5.0733          | 1.0    |
| 4.7729        | 0.32  | 400  | 5.0188          | 1.0    |
| 4.7749        | 0.4   | 500  | 4.9321          | 1.0    |
| 4.7657        | 0.48  | 600  | 4.8467          | 1.0    |
| 4.7006        | 0.56  | 700  | 4.8097          | 1.0    |
| 4.6775        | 0.64  | 800  | 4.8150          | 1.0    |
| 4.6484        | 0.72  | 900  | 4.7064          | 1.0    |
| 4.6009        | 0.8   | 1000 | 4.7248          | 1.0    |
| 4.5753        | 0.88  | 1100 | 4.6097          | 0.9991 |
| 4.533         | 0.96  | 1200 | 4.5760          | 1.0    |
| 4.4915        | 1.04  | 1300 | 4.5454          | 0.9845 |
| 4.436         | 1.12  | 1400 | 4.4345          | 0.9842 |
| 4.3636        | 1.2   | 1500 | 4.3722          | 0.9363 |
| 4.3186        | 1.28  | 1600 | 4.2747          | 0.9566 |
| 4.2326        | 1.36  | 1700 | 4.0707          | 0.9416 |
| 4.0018        | 1.44  | 1800 | 3.6969          | 0.7459 |
| 3.6566        | 1.52  | 1900 | 3.2351          | 0.5922 |
| 3.3079        | 1.6   | 2000 | 2.9201          | 0.5560 |
| 3.1056        | 1.68  | 2100 | 2.6958          | 0.5182 |
| 2.9577        | 1.76  | 2200 | 2.5580          | 0.4942 |
| 2.7556        | 1.84  | 2300 | 2.3948          | 0.4671 |
| 2.6682        | 1.92  | 2400 | 2.2875          | 0.4521 |
| 2.5461        | 2.0   | 2500 | 2.1791          | 0.4386 |
| 2.4496        | 2.08  | 2600 | 2.0957          | 0.4230 |
| 2.3548        | 2.16  | 2700 | 2.0157          | 0.4132 |
| 2.2973        | 2.24  | 2800 | 1.9433          | 0.4010 |
| 2.2631        | 2.32  | 2900 | 1.8848          | 0.3926 |
| 2.1837        | 2.4   | 3000 | 1.8301          | 0.3827 |
| 2.1427        | 2.48  | 3100 | 1.7783          | 0.3738 |
| 2.0955        | 2.56  | 3200 | 1.7377          | 0.3678 |
| 2.0393        | 2.64  | 3300 | 1.6954          | 0.3616 |
| 2.0162        | 2.72  | 3400 | 1.6446          | 0.3576 |
| 1.9577        | 2.8   | 3500 | 1.6098          | 0.3507 |
| 1.9501        | 2.88  | 3600 | 1.5772          | 0.3427 |
| 1.8684        | 2.96  | 3700 | 1.5502          | 0.3361 |
| 1.8625        | 3.04  | 3800 | 1.5222          | 0.3290 |
| 1.8252        | 3.12  | 3900 | 1.5000          | 0.3265 |
| 1.8299        | 3.2   | 4000 | 1.4743          | 0.3201 |
| 1.758         | 3.28  | 4100 | 1.4529          | 0.3156 |
| 1.7731        | 3.36  | 4200 | 1.4388          | 0.3137 |
| 1.7579        | 3.44  | 4300 | 1.4195          | 0.3076 |
| 1.7205        | 3.52  | 4400 | 1.4120          | 0.3084 |
| 1.6997        | 3.6   | 4500 | 1.3986          | 0.3055 |
| 1.7536        | 3.68  | 4600 | 1.3830          | 0.3039 |
| 1.6927        | 3.76  | 4700 | 1.3755          | 0.3025 |
| 1.6604        | 3.84  | 4800 | 1.3701          | 0.3010 |
| 1.6599        | 3.92  | 4900 | 1.3686          | 0.3002 |
| 1.6567        | 4.0   | 5000 | 1.3680          | 0.3009 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.13.0
- Tokenizers 0.15.0
