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: wav2vec2-large-xls-r-300m-ko_Y2
  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. -->

# wav2vec2-large-xls-r-300m-ko_Y2

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7543
- Cer: 63.2284

## 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: 0.0003
- 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 30.4598       | 0.13  | 200  | 4.8628          | 100.0   |
| 4.9057        | 0.26  | 400  | 4.6582          | 100.0   |
| 4.8545        | 0.39  | 600  | 4.6698          | 100.0   |
| 4.8629        | 0.52  | 800  | 4.6900          | 100.0   |
| 4.8065        | 0.64  | 1000 | 4.6762          | 100.0   |
| 4.8111        | 0.77  | 1200 | 4.6486          | 100.0   |
| 4.7942        | 0.9   | 1400 | 4.8506          | 100.0   |
| 4.741         | 1.03  | 1600 | 4.6609          | 100.0   |
| 4.7087        | 1.16  | 1800 | 4.6844          | 100.0   |
| 4.6709        | 1.29  | 2000 | 4.5644          | 100.0   |
| 4.5943        | 1.42  | 2200 | 4.5284          | 100.0   |
| 4.4217        | 1.55  | 2400 | 4.3024          | 99.8297 |
| 3.9213        | 1.68  | 2600 | 3.9734          | 87.5822 |
| 3.4005        | 1.81  | 2800 | 3.5616          | 75.6931 |
| 2.9827        | 1.93  | 3000 | 3.4234          | 70.6473 |
| 2.7042        | 2.06  | 3200 | 3.3518          | 70.1304 |
| 2.5051        | 2.19  | 3400 | 3.0818          | 70.3947 |
| 2.3372        | 2.32  | 3600 | 2.8767          | 65.0082 |
| 2.2472        | 2.45  | 3800 | 2.9150          | 68.0804 |
| 2.1194        | 2.58  | 4000 | 2.8689          | 64.7380 |
| 2.0699        | 2.71  | 4200 | 2.8134          | 64.4149 |
| 1.9761        | 2.84  | 4400 | 2.8036          | 64.4796 |
| 1.9927        | 2.97  | 4600 | 2.7543          | 63.2284 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
