|
--- |
|
language: |
|
- sv-SE |
|
license: apache-2.0 |
|
tags: |
|
- automatic-speech-recognition |
|
- generated_from_trainer |
|
- hf-asr-leaderboard |
|
- hello |
|
- model_for_talk |
|
- mozilla-foundation/common_voice_7_0 |
|
- robust-speech-event |
|
- sv |
|
datasets: |
|
- mozilla-foundation/common_voice_7_0 |
|
model-index: |
|
- name: XLS-R-300M - Swedish |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Common Voice 7 |
|
type: mozilla-foundation/common_voice_7_0 |
|
args: sv-SE |
|
metrics: |
|
- name: Test WER |
|
type: wer |
|
value: 16.98 |
|
- name: Test CER |
|
type: cer |
|
value: 5.66 |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Robust Speech Event - Dev Data |
|
type: speech-recognition-community-v2/dev_data |
|
args: sv |
|
metrics: |
|
- name: Test WER |
|
type: wer |
|
value: 27.01 |
|
- name: Test CER |
|
type: cer |
|
value: 13.14 |
|
--- |
|
|
|
<!-- 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-SV |
|
|
|
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 - SV-SE dataset. |
|
It achieves the following results on the evaluation set: |
|
|
|
- Loss: 0.3171 |
|
- Wer: 0.2468 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 2000 |
|
- num_epochs: 50.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:| |
|
| 3.3349 | 1.45 | 500 | 3.2858 | 1.0 | |
|
| 2.9298 | 2.91 | 1000 | 2.9225 | 1.0000 | |
|
| 2.0839 | 4.36 | 1500 | 1.1546 | 0.8295 | |
|
| 1.7093 | 5.81 | 2000 | 0.6827 | 0.5701 | |
|
| 1.5855 | 7.27 | 2500 | 0.5597 | 0.4947 | |
|
| 1.4831 | 8.72 | 3000 | 0.4923 | 0.4527 | |
|
| 1.4416 | 10.17 | 3500 | 0.4670 | 0.4270 | |
|
| 1.3848 | 11.63 | 4000 | 0.4341 | 0.3980 | |
|
| 1.3749 | 13.08 | 4500 | 0.4203 | 0.4011 | |
|
| 1.3311 | 14.53 | 5000 | 0.4310 | 0.3961 | |
|
| 1.317 | 15.99 | 5500 | 0.3898 | 0.4322 | |
|
| 1.2799 | 17.44 | 6000 | 0.3806 | 0.3572 | |
|
| 1.2771 | 18.89 | 6500 | 0.3828 | 0.3427 | |
|
| 1.2451 | 20.35 | 7000 | 0.3702 | 0.3359 | |
|
| 1.2182 | 21.8 | 7500 | 0.3685 | 0.3270 | |
|
| 1.2152 | 23.26 | 8000 | 0.3650 | 0.3308 | |
|
| 1.1837 | 24.71 | 8500 | 0.3568 | 0.3187 | |
|
| 1.1721 | 26.16 | 9000 | 0.3659 | 0.3249 | |
|
| 1.1764 | 27.61 | 9500 | 0.3547 | 0.3145 | |
|
| 1.1606 | 29.07 | 10000 | 0.3514 | 0.3104 | |
|
| 1.1431 | 30.52 | 10500 | 0.3469 | 0.3062 | |
|
| 1.1047 | 31.97 | 11000 | 0.3313 | 0.2979 | |
|
| 1.1315 | 33.43 | 11500 | 0.3298 | 0.2992 | |
|
| 1.1022 | 34.88 | 12000 | 0.3296 | 0.2973 | |
|
| 1.0935 | 36.34 | 12500 | 0.3278 | 0.2926 | |
|
| 1.0676 | 37.79 | 13000 | 0.3208 | 0.2868 | |
|
| 1.0571 | 39.24 | 13500 | 0.3322 | 0.2885 | |
|
| 1.0536 | 40.7 | 14000 | 0.3245 | 0.2831 | |
|
| 1.0525 | 42.15 | 14500 | 0.3285 | 0.2826 | |
|
| 1.0464 | 43.6 | 15000 | 0.3223 | 0.2796 | |
|
| 1.0415 | 45.06 | 15500 | 0.3166 | 0.2774 | |
|
| 1.0356 | 46.51 | 16000 | 0.3177 | 0.2746 | |
|
| 1.04 | 47.96 | 16500 | 0.3150 | 0.2735 | |
|
| 1.0209 | 49.42 | 17000 | 0.3175 | 0.2731 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.16.0.dev0 |
|
- Pytorch 1.10.0+cu102 |
|
- Datasets 1.17.1.dev0 |
|
- 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 hf-test/xls-r-300m-sv --dataset mozilla-foundation/common_voice_7_0 --config sv-SE --split test |
|
``` |
|
|
|
2. To evaluate on `speech-recognition-community-v2/dev_data` |
|
|
|
```bash |
|
python eval.py --model_id hf-test/xls-r-300m-sv --dataset speech-recognition-community-v2/dev_data --config sv --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 = "hf-test/xls-r-300m-sv" |
|
|
|
sample_iter = iter(load_dataset("mozilla-foundation/common_voice_7_0", "sv-SE", 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 |
|
# => "jag lämnade grovjobbet åt honom" |
|
``` |
|
|
|
### Eval results on Common Voice 7 "test" (WER): |
|
|
|
| Without LM | With LM (run `./eval.py`) | |
|
|---|---| |
|
| 24.68 | 16.98 | |
|
|
|
|
|
|
