metadata
language:
- cy
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- cy
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: XLS-R-300M - Welsh
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: cy
metrics:
- name: Test WER
type: wer
value: 31.003
- name: Test CER
type: cer
value: 7.775
wav2vec2-large-xls-r-300m-welsh
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - CY dataset. It achieves the following results on the evaluation set:
- Loss: 0.2650
- Wer: 0.2702
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: 7e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 3000
- num_epochs: 50.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.3454 | 8.2 | 3000 | 0.4926 | 0.5703 |
1.1202 | 16.39 | 6000 | 0.3529 | 0.3944 |
1.0058 | 24.59 | 9000 | 0.3143 | 0.3341 |
0.9287 | 32.79 | 12000 | 0.2896 | 0.2980 |
0.8849 | 40.98 | 15000 | 0.2727 | 0.2798 |
0.8665 | 49.18 | 18000 | 0.2662 | 0.2696 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0