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-korean_senior-colab
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-large-xls-r-300m-korean_senior-colab

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: 1.3662
- Cer: 0.3521

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 23.3703       | 0.13  | 200  | 4.6540          | 1.0    |
| 4.5902        | 0.26  | 400  | 4.6068          | 1.0    |
| 4.5584        | 0.39  | 600  | 4.6189          | 1.0    |
| 4.5187        | 0.52  | 800  | 4.5712          | 1.0    |
| 4.4877        | 0.64  | 1000 | 4.6354          | 1.0    |
| 4.4415        | 0.77  | 1200 | 4.4681          | 1.0    |
| 4.2243        | 0.9   | 1400 | 4.0606          | 0.8462 |
| 3.4216        | 1.03  | 1600 | 3.0853          | 0.7218 |
| 2.7586        | 1.16  | 1800 | 2.6957          | 0.6083 |
| 2.355         | 1.29  | 2000 | 2.4372          | 0.5711 |
| 2.1589        | 1.42  | 2200 | 2.2552          | 0.5251 |
| 2.0473        | 1.55  | 2400 | 2.1381          | 0.5227 |
| 1.8895        | 1.68  | 2600 | 1.9748          | 0.4967 |
| 1.7995        | 1.81  | 2800 | 2.0369          | 0.4985 |
| 1.754         | 1.93  | 3000 | 1.8281          | 0.4578 |
| 1.6027        | 2.06  | 3200 | 1.8280          | 0.4539 |
| 1.5043        | 2.19  | 3400 | 1.7238          | 0.4285 |
| 1.4397        | 2.32  | 3600 | 1.6137          | 0.4171 |
| 1.3416        | 2.45  | 3800 | 1.5148          | 0.3874 |
| 1.2632        | 2.58  | 4000 | 1.5120          | 0.3840 |
| 1.204         | 2.71  | 4200 | 1.4443          | 0.3741 |
| 1.1655        | 2.84  | 4400 | 1.3976          | 0.3617 |
| 1.1657        | 2.97  | 4600 | 1.3662          | 0.3521 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
