Edit model card

wav2vec2-xls-r-300m-ab-CV8

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2105
  • Wer: 0.5474

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: 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: 300
  • num_epochs: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
4.7729 0.63 500 3.0624 1.0021
2.7348 1.26 1000 1.0460 0.9815
1.2756 1.9 1500 0.4618 0.8309
1.0419 2.53 2000 0.3725 0.7449
0.9491 3.16 2500 0.3368 0.7345
0.9006 3.79 3000 0.3014 0.6936
0.8519 4.42 3500 0.2852 0.6767
0.8243 5.06 4000 0.2701 0.6504
0.7902 5.69 4500 0.2641 0.6221
0.7767 6.32 5000 0.2549 0.6192
0.7516 6.95 5500 0.2515 0.6179
0.737 7.59 6000 0.2408 0.5963
0.7217 8.22 6500 0.2429 0.6261
0.7101 8.85 7000 0.2366 0.5687
0.6922 9.48 7500 0.2277 0.5680
0.6866 10.11 8000 0.2242 0.5847
0.6703 10.75 8500 0.2222 0.5803
0.6649 11.38 9000 0.2247 0.5765
0.6513 12.01 9500 0.2182 0.5644
0.6369 12.64 10000 0.2128 0.5508
0.6425 13.27 10500 0.2132 0.5514
0.6399 13.91 11000 0.2116 0.5495
0.6208 14.54 11500 0.2105 0.5474

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.1
  • Tokenizers 0.10.3
Downloads last month
2
Hosted inference API
or or
This model can be loaded on the Inference API on-demand.

Dataset used to train emre/wav2vec2-xls-r-300m-ab-CV8

Evaluation results