|
--- |
|
language: |
|
- sl |
|
license: apache-2.0 |
|
tags: |
|
- automatic-speech-recognition |
|
- generated_from_trainer |
|
- hf-asr-leaderboard |
|
- mozilla-foundation/common_voice_8_0 |
|
- robust-speech-event |
|
datasets: |
|
- mozilla-foundation/common_voice_8_0 |
|
model-index: |
|
- name: XLS-R-300M - Slovenian |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Common Voice 8 |
|
type: mozilla-foundation/common_voice_8_0 |
|
args: sl |
|
metrics: |
|
- name: Test WER |
|
type: wer |
|
value: 12.736 |
|
- name: Test CER |
|
type: cer |
|
value: 3.605 |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Robust Speech Event - Dev Data |
|
type: speech-recognition-community-v2/dev_data |
|
args: sl |
|
metrics: |
|
- name: Test WER |
|
type: wer |
|
value: 45.587 |
|
- name: Test CER |
|
type: cer |
|
value: 20.886 |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Robust Speech Event - Test Data |
|
type: speech-recognition-community-v2/eval_data |
|
args: sl |
|
metrics: |
|
- name: Test WER |
|
type: wer |
|
value: 45.42 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# XLS-R-300M - Slovenian |
|
|
|
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 - SL dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2578 |
|
- Wer: 0.2273 |
|
|
|
## 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: 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: 1000 |
|
- num_epochs: 60.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 3.1829 | 4.88 | 400 | 3.1228 | 1.0 | |
|
| 2.8675 | 9.76 | 800 | 2.8616 | 0.9993 | |
|
| 1.583 | 14.63 | 1200 | 0.6392 | 0.6239 | |
|
| 1.1959 | 19.51 | 1600 | 0.3602 | 0.3651 | |
|
| 1.0276 | 24.39 | 2000 | 0.3021 | 0.2981 | |
|
| 0.9671 | 29.27 | 2400 | 0.2872 | 0.2739 | |
|
| 0.873 | 34.15 | 2800 | 0.2593 | 0.2459 | |
|
| 0.8513 | 39.02 | 3200 | 0.2617 | 0.2473 | |
|
| 0.8132 | 43.9 | 3600 | 0.2548 | 0.2426 | |
|
| 0.7935 | 48.78 | 4000 | 0.2637 | 0.2353 | |
|
| 0.7565 | 53.66 | 4400 | 0.2629 | 0.2322 | |
|
| 0.7359 | 58.54 | 4800 | 0.2579 | 0.2253 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.17.0.dev0 |
|
- Pytorch 1.10.2+cu102 |
|
- Datasets 1.18.2.dev0 |
|
- Tokenizers 0.11.0 |
|
|
|
#### Evaluation Commands |
|
1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test` |
|
|
|
```bash |
|
python eval.py --model_id anuragshas/wav2vec2-xls-r-300m-sl-cv8-with-lm --dataset mozilla-foundation/common_voice_8_0 --config sl --split test |
|
``` |
|
|
|
2. To evaluate on `speech-recognition-community-v2/dev_data` |
|
|
|
```bash |
|
python eval.py --model_id anuragshas/wav2vec2-xls-r-300m-sl-cv8-with-lm --dataset speech-recognition-community-v2/dev_data --config sl --split validation --chunk_length_s 5.0 --stride_length_s 1.0 |
|
``` |
|
|
|
### Inference With LM |
|
|
|
```python |
|
import torch |
|
from datasets import load_dataset |
|
from transformers import AutoModelForCTC, AutoProcessor |
|
import torchaudio.functional as F |
|
model_id = "anuragshas/wav2vec2-xls-r-300m-sl-cv8-with-lm" |
|
sample_iter = iter(load_dataset("mozilla-foundation/common_voice_8_0", "sl", split="test", streaming=True, use_auth_token=True)) |
|
sample = next(sample_iter) |
|
resampled_audio = F.resample(torch.tensor(sample["audio"]["array"]), 48_000, 16_000).numpy() |
|
model = AutoModelForCTC.from_pretrained(model_id) |
|
processor = AutoProcessor.from_pretrained(model_id) |
|
input_values = processor(resampled_audio, return_tensors="pt").input_values |
|
with torch.no_grad(): |
|
logits = model(input_values).logits |
|
transcription = processor.batch_decode(logits.numpy()).text |
|
# => "zmago je divje od letel s helikopterjem visoko vzrak" |
|
``` |
|
|
|
### Eval results on Common Voice 8 "test" (WER): |
|
|
|
| Without LM | With LM (run `./eval.py`) | |
|
|---|---| |
|
| 19.938 | 12.736 | |
