|
--- |
|
language: |
|
- pa |
|
- pa-IN |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
- robust-speech-event |
|
- hf-asr-leaderboard |
|
datasets: |
|
- mozilla-foundation/common_voice_7_0 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: XLS-R-300M - Punjabi |
|
results: |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Speech Recognition |
|
dataset: |
|
type: mozilla-foundation/common_voice_7_0 |
|
name: Common Voice 7 |
|
args: pa-IN |
|
metrics: |
|
- type: wer |
|
value: 45.611 |
|
name: Test WER |
|
- name: Test CER |
|
type: cer |
|
value: 15.584 |
|
--- |
|
|
|
<!-- 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 - Punjabi |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.2548 |
|
- Wer: 0.5677 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.12 |
|
- num_epochs: 120 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:------:|:----:|:---------------:|:------:| |
|
| 6.4804 | 16.65 | 400 | 1.8461 | 1.0 | |
|
| 0.474 | 33.33 | 800 | 1.1018 | 0.6624 | |
|
| 0.1389 | 49.98 | 1200 | 1.1918 | 0.6103 | |
|
| 0.0919 | 66.65 | 1600 | 1.1889 | 0.6058 | |
|
| 0.0657 | 83.33 | 2000 | 1.2266 | 0.5931 | |
|
| 0.0479 | 99.98 | 2400 | 1.2512 | 0.5902 | |
|
| 0.0355 | 116.65 | 2800 | 1.2548 | 0.5677 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.15.0 |
|
- Pytorch 1.10.0+cu111 |
|
- Datasets 1.18.0 |
|
- Tokenizers 0.10.3 |
|
|
|
|
|
#### Evaluation Commands |
|
1. To evaluate on `mozilla-foundation/common_voice_7_0` with split `test` |
|
|
|
```bash |
|
python eval.py --model_id anuragshas/wav2vec2-large-xls-r-300m-pa-in --dataset mozilla-foundation/common_voice_7_0 --config pa-IN --split test |
|
``` |
|
|
|
|
|
### 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-large-xls-r-300m-pa-in" |
|
sample_iter = iter(load_dataset("mozilla-foundation/common_voice_7_0", "pa-IN", 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 |
|
# => "ਉਨ੍ਹਾਂ ਨੇ ਸਾਰੇ ਤੇਅਰਵੇ ਵੱਖਰੀ ਕਿਸਮ ਦੇ ਕੀਤੇ ਹਨ" |
|
``` |
|
|
|
### Eval results on Common Voice 7 "test" (WER): |
|
|
|
| Without LM | With LM (run `./eval.py`) | |
|
|---|---| |
|
| 51.968 | 45.611 | |
|
|