|
--- |
|
language: |
|
- cv |
|
license: apache-2.0 |
|
tags: |
|
- automatic-speech-recognition |
|
- mozilla-foundation/common_voice_7_0 |
|
- generated_from_trainer |
|
- cv |
|
- robust-speech-event |
|
- model_for_talk |
|
- hf-asr-leaderboard |
|
datasets: |
|
- mozilla-foundation/common_voice_7_0 |
|
model-index: |
|
- name: XLS-R-300M - Chuvash |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Common Voice 7 |
|
type: mozilla-foundation/common_voice_7_0 |
|
args: cv |
|
metrics: |
|
- name: Test WER |
|
type: wer |
|
value: 60.31 |
|
- name: Test CER |
|
type: cer |
|
value: 15.08 |
|
--- |
|
|
|
<!-- 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-chuvash |
|
|
|
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_7_0 - CV dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7651 |
|
- Wer: 0.6166 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 1.8032 | 8.77 | 500 | 0.8059 | 0.8352 | |
|
| 1.2608 | 17.54 | 1000 | 0.5828 | 0.6769 | |
|
| 1.1337 | 26.32 | 1500 | 0.6892 | 0.6908 | |
|
| 1.0457 | 35.09 | 2000 | 0.7077 | 0.6781 | |
|
| 0.97 | 43.86 | 2500 | 0.5993 | 0.6228 | |
|
| 0.8767 | 52.63 | 3000 | 0.7213 | 0.6604 | |
|
| 0.8223 | 61.4 | 3500 | 0.8161 | 0.6968 | |
|
| 0.7441 | 70.18 | 4000 | 0.7057 | 0.6184 | |
|
| 0.7011 | 78.95 | 4500 | 0.7027 | 0.6024 | |
|
| 0.6542 | 87.72 | 5000 | 0.7092 | 0.5979 | |
|
| 0.6081 | 96.49 | 5500 | 0.7917 | 0.6324 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.16.0.dev0 |
|
- Pytorch 1.10.1+cu102 |
|
- Datasets 1.17.1.dev0 |
|
- Tokenizers 0.11.0 |
|
|