|
--- |
|
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 |
|
|
