metadata

library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
datasets:
  - common_voice_17_0
metrics:
  - wer
model-index:
  - name: wav2vec2_common_voice17_finetuning
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_17_0
          type: common_voice_17_0
          config: ro
          split: test
          args: ro
        metrics:
          - name: Wer
            type: wer
            value: 1

wav2vec2_common_voice17_finetuning

This model is a fine-tuned version of facebook/wav2vec2-base on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.4054
Wer: 1.0

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: 32
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.6577	3.5461	1000	0.4788	0.9997
0.2893	7.0922	2000	0.4086	1.0
0.1997	10.6383	3000	0.4135	0.9997
0.156	14.1844	4000	0.4051	0.9992
0.138	17.7305	5000	0.4054	1.0

Framework versions

Transformers 4.49.0
Pytorch 2.4.1+cu124
Datasets 2.21.0
Tokenizers 0.21.0