metadata

language:
  - cy
license: apache-2.0
tags:
  - automatic-speech-recognition
  - cy
  - generated_from_trainer
  - hf-asr-leaderboard
  - model_for_talk
  - mozilla-foundation/common_voice_7_0
  - robust-speech-event
datasets:
  - mozilla-foundation/common_voice_7_0
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