|
--- |
|
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: |
|
- mozilla-foundation/common_voice_8_0 |
|
model-index: |
|
- name: wav2vec2-xls-r-1b-hy-cv |
|
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: 12.246920571994902 |
|
name: WER LM |
|
- type: cer |
|
value: 2.513653497966816 |
|
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: 46.56 |
|
- 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: 35.98 |
|
--- |
|
|
|
<!-- 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 MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - UK dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1747 |
|
- Wer: 0.2107 |
|
- Cer: 0.0408 |
|
|
|
## 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: 8e-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: 8000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
|
| 1.3719 | 4.35 | 500 | 0.3389 | 0.4236 | 0.0833 | |
|
| 1.1361 | 8.7 | 1000 | 0.2309 | 0.3162 | 0.0630 | |
|
| 1.0517 | 13.04 | 1500 | 0.2166 | 0.3056 | 0.0597 | |
|
| 1.0118 | 17.39 | 2000 | 0.2141 | 0.2784 | 0.0557 | |
|
| 0.9922 | 21.74 | 2500 | 0.2231 | 0.2941 | 0.0594 | |
|
| 0.9929 | 26.09 | 3000 | 0.2171 | 0.2892 | 0.0587 | |
|
| 0.9485 | 30.43 | 3500 | 0.2236 | 0.2956 | 0.0599 | |
|
| 0.9573 | 34.78 | 4000 | 0.2314 | 0.3043 | 0.0616 | |
|
| 0.9195 | 39.13 | 4500 | 0.2169 | 0.2812 | 0.0580 | |
|
| 0.8915 | 43.48 | 5000 | 0.2109 | 0.2780 | 0.0560 | |
|
| 0.8449 | 47.83 | 5500 | 0.2050 | 0.2534 | 0.0514 | |
|
| 0.8028 | 52.17 | 6000 | 0.2032 | 0.2456 | 0.0492 | |
|
| 0.7881 | 56.52 | 6500 | 0.1890 | 0.2380 | 0.0469 | |
|
| 0.7423 | 60.87 | 7000 | 0.1816 | 0.2245 | 0.0442 | |
|
| 0.7248 | 65.22 | 7500 | 0.1789 | 0.2165 | 0.0422 | |
|
| 0.6993 | 69.57 | 8000 | 0.1747 | 0.2107 | 0.0408 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.17.0.dev0 |
|
- Pytorch 1.10.2+cu102 |
|
- Datasets 1.18.2.dev0 |
|
- Tokenizers 0.11.0 |
|
|
