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---
license: apache-2.0
tags:
- automatic-speech-recognition
- google/fleurs
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: facebook/wav2vec2-xls-r-1b
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: GOOGLE/FLEURS - PS_AF
type: fleurs
config: ps_af
split: test
args: 'Config: ps_af, Training split: train+validation, Eval split: test'
metrics:
- name: Wer
type: wer
value: 0.9294849931787176
---
<!-- 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. -->
# facebook/wav2vec2-xls-r-1b
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the GOOGLE/FLEURS - PS_AF dataset.
It achieves the following results on the evaluation set:
- Loss: 4.1921
- Wer: 0.9295
- Cer: 0.9608
## 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: 7.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 1000
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:------:|:---------------:|:------:|
| 19.9558 | 1.27 | 100 | 3.2660 | 20.9197 | 1.0 |
| 19.7186 | 2.53 | 200 | 1.1692 | 19.2447 | 1.0 |
| 15.203 | 3.8 | 300 | 0.9687 | 15.0053 | 0.9998 |
| 6.4303 | 5.06 | 400 | 0.9911 | 6.5437 | 0.9632 |
| 4.5712 | 6.33 | 500 | 0.9546 | 4.9040 | 0.9323 |
| 3.3986 | 12.66 | 1000 | 4.1921 | 0.9295 | 0.9608 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|