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---
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
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