README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - xtreme_s
metrics:
  - wer
base_model: facebook/wav2vec2-large-xlsr-53
model-index:
  - name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod6
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: xtreme_s
          type: xtreme_s
          config: fleurs.id_id
          split: test
          args: fleurs.id_id
        metrics:
          - type: wer
            value: 0.5287382128423889
            name: Wer

wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod6

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the xtreme_s dataset. It achieves the following results on the evaluation set:

• Loss: 0.9531
• Wer: 0.5287

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: 0.001
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 600
• num_epochs: 90
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.2079	18.18	300	2.8502	1.0
1.5727	36.36	600	0.8489	0.6749
0.1925	54.55	900	1.0067	0.5868
0.0963	72.73	1200	0.9531	0.5287

Framework versions

• Transformers 4.37.2
• Pytorch 2.2.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1