metadata

license: apache-2.0
base_model: nutella-toast/wav2vec2-large-xls-r-ssw
tags:
  - generated_from_trainer
datasets:
  - ml-superb-subset
metrics:
  - wer
model-index:
  - name: wav2vec2-large-xls-r-ssw
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: ml-superb-subset
          type: ml-superb-subset
          config: ssw
          split: dev
          args: ssw
        metrics:
          - name: Wer
            type: wer
            value: 0.940809968847352

wav2vec2-large-xls-r-ssw

This model is a fine-tuned version of nutella-toast/wav2vec2-large-xls-r-ssw on the ml-superb-subset dataset. It achieves the following results on the evaluation set:

Loss: 1.0000
Wer: 0.9408

Model description

Finetuned version of vanilla Wav2Vec2 for CS224S.

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: 0.0003
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.3831	1.0471	100	1.3053	1.0
1.2606	2.0942	200	1.1802	0.9720
1.0789	3.1414	300	1.0889	1.0405
0.9249	4.1885	400	1.0000	0.9408

Framework versions

Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1