|
--- |
|
language: |
|
- uk |
|
license: apache-2.0 |
|
tags: |
|
- automatic-speech-recognition |
|
- generated_from_trainer |
|
- hf-asr-leaderboard |
|
- mozilla-foundation/common_voice_8_0 |
|
- robust-speech-event |
|
datasets: |
|
- common_voice |
|
model-index: |
|
- name: wav2vec2-xls-r-1b-hy |
|
results: |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Speech Recognition |
|
dataset: |
|
type: mozilla-foundation/common_voice_8_0 |
|
name: Common Voice uk |
|
args: uk |
|
metrics: |
|
- type: wer |
|
value: 10.406342913776015 |
|
name: WER LM |
|
- type: cer |
|
value: 2.0387492208601703 |
|
name: CER LM |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Robust Speech Event - Dev Data |
|
type: speech-recognition-community-v2/dev_data |
|
args: uk |
|
metrics: |
|
- name: Test WER |
|
type: wer |
|
value: 40.57 |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Robust Speech Event - Test Data |
|
type: speech-recognition-community-v2/eval_data |
|
args: uk |
|
metrics: |
|
- name: Test WER |
|
type: wer |
|
value: 28.95 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the /WORKSPACE/DATA/UK/COMPOSED_DATASET/ - NA dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1092 |
|
- Wer: 0.1752 |
|
- Cer: 0.0323 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 64 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 128 |
|
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- training_steps: 12000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
|
| 1.7005 | 1.61 | 500 | 0.4082 | 0.5584 | 0.1164 | |
|
| 1.1555 | 3.22 | 1000 | 0.2020 | 0.2953 | 0.0557 | |
|
| 1.0927 | 4.82 | 1500 | 0.1708 | 0.2584 | 0.0480 | |
|
| 1.0707 | 6.43 | 2000 | 0.1563 | 0.2405 | 0.0450 | |
|
| 1.0728 | 8.04 | 2500 | 0.1620 | 0.2442 | 0.0463 | |
|
| 1.0268 | 9.65 | 3000 | 0.1588 | 0.2378 | 0.0458 | |
|
| 1.0328 | 11.25 | 3500 | 0.1466 | 0.2352 | 0.0442 | |
|
| 1.0249 | 12.86 | 4000 | 0.1552 | 0.2341 | 0.0449 | |
|
| 1.016 | 14.47 | 4500 | 0.1602 | 0.2435 | 0.0473 | |
|
| 1.0164 | 16.08 | 5000 | 0.1491 | 0.2337 | 0.0444 | |
|
| 0.9935 | 17.68 | 5500 | 0.1539 | 0.2373 | 0.0458 | |
|
| 0.9626 | 19.29 | 6000 | 0.1458 | 0.2305 | 0.0434 | |
|
| 0.9505 | 20.9 | 6500 | 0.1368 | 0.2157 | 0.0407 | |
|
| 0.9389 | 22.51 | 7000 | 0.1437 | 0.2231 | 0.0426 | |
|
| 0.9129 | 24.12 | 7500 | 0.1313 | 0.2076 | 0.0394 | |
|
| 0.9118 | 25.72 | 8000 | 0.1292 | 0.2040 | 0.0384 | |
|
| 0.8848 | 27.33 | 8500 | 0.1299 | 0.2028 | 0.0384 | |
|
| 0.8667 | 28.94 | 9000 | 0.1228 | 0.1945 | 0.0367 | |
|
| 0.8641 | 30.55 | 9500 | 0.1223 | 0.1939 | 0.0364 | |
|
| 0.8516 | 32.15 | 10000 | 0.1184 | 0.1876 | 0.0349 | |
|
| 0.8379 | 33.76 | 10500 | 0.1137 | 0.1821 | 0.0338 | |
|
| 0.8235 | 35.37 | 11000 | 0.1127 | 0.1779 | 0.0331 | |
|
| 0.8112 | 36.98 | 11500 | 0.1103 | 0.1766 | 0.0327 | |
|
| 0.8069 | 38.59 | 12000 | 0.1092 | 0.1752 | 0.0323 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.17.0.dev0 |
|
- Pytorch 1.10.2 |
|
- Datasets 1.18.4.dev0 |
|
- Tokenizers 0.11.0 |
|
|
