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---
language:
- bas
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- bas
- robust-speech-event
- model_for_talk
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: XLS-R-300M - Basaa
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: bas
metrics:
- name: Test WER
type: wer
value: 38.057
- name: Test CER
type: cer
value: 11.233
---
<!-- 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-basaa-cv8
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - BAS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4648
- Wer: 0.5472
## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9421 | 12.82 | 500 | 2.8894 | 1.0 |
| 1.1872 | 25.64 | 1000 | 0.6688 | 0.7460 |
| 0.8894 | 38.46 | 1500 | 0.4868 | 0.6516 |
| 0.769 | 51.28 | 2000 | 0.4960 | 0.6507 |
| 0.6936 | 64.1 | 2500 | 0.4781 | 0.5384 |
| 0.624 | 76.92 | 3000 | 0.4643 | 0.5430 |
| 0.5966 | 89.74 | 3500 | 0.4530 | 0.5591 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0
|