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---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-vi-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: vi
split: test
args: vi
metrics:
- name: Wer
type: wer
value: 0.629702753098607
---
<!-- 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-vi-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5942
- Wer: 0.6297
## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 7.514 | 4.6 | 400 | 3.3352 | 1.0 |
| 0.9018 | 9.2 | 800 | 1.4660 | 0.7177 |
| 0.2284 | 13.79 | 1200 | 1.5156 | 0.6873 |
| 0.138 | 18.39 | 1600 | 1.5294 | 0.6599 |
| 0.0959 | 22.99 | 2000 | 1.5876 | 0.6485 |
| 0.0703 | 27.59 | 2400 | 1.5942 | 0.6297 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7.dev0
- Tokenizers 0.14.1