metadata

license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
datasets:
  - librispeech_asr_dummy
metrics:
  - wer
model-index:
  - name: wav2vec2-base-librispeech
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: librispeech_asr_dummy
          type: librispeech_asr_dummy
          config: clean
          split: None
          args: clean
        metrics:
          - name: Wer
            type: wer
            value: 0.4069767441860465

wav2vec2-base-librispeech

This model is a fine-tuned version of facebook/wav2vec2-base on the librispeech_asr_dummy dataset. It achieves the following results on the evaluation set:

Loss: 0.9548
Wer: 0.4070

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: 0.0001
train_batch_size: 4
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 150
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.4865	29.41	500	3.5010	1.0
1.112	58.82	1000	1.0382	0.4767
0.111	88.24	1500	0.9833	0.5116
0.0438	117.65	2000	0.9302	0.4302
0.0241	147.06	2500	0.9548	0.4070

Framework versions

Transformers 4.36.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2