Edit model card

wav2vec2-xls-r-300m-en-ar-fr-es

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: 0.8565
  • Wer: 0.4869

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: 0.0003
  • 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: 500
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
6.3938 0.59 400 3.3703 1.0
2.353 1.18 800 0.9696 0.7809
0.9859 1.77 1200 0.7031 0.6515
0.7685 2.35 1600 0.6575 0.6321
0.6892 2.94 2000 0.6030 0.5927
0.5866 3.53 2400 0.5552 0.5541
0.5496 4.12 2800 0.5805 0.5503
0.4897 4.71 3200 0.5526 0.5335
0.4671 5.3 3600 0.5622 0.5507
0.4346 5.89 4000 0.5641 0.5312
0.3859 6.48 4400 0.5685 0.5071
0.3728 7.06 4800 0.6106 0.5157
0.3243 7.65 5200 0.6782 0.5270
0.3073 8.24 5600 0.6121 0.5232
0.2748 8.83 6000 0.6318 0.5209
0.25 9.42 6400 0.6334 0.4906
0.2477 10.01 6800 0.6403 0.5169
0.2125 10.6 7200 0.6498 0.5080
0.1997 11.18 7600 0.7029 0.5153
0.1803 11.77 8000 0.6796 0.5193
0.1644 12.36 8400 0.7320 0.5080
0.1609 12.95 8800 0.6705 0.5081
0.1419 13.54 9200 0.7108 0.5120
0.1375 14.13 9600 0.7570 0.4909
0.1265 14.72 10000 0.7681 0.5044
0.1152 15.31 10400 0.8180 0.5011
0.1094 15.89 10800 0.7753 0.4947
0.0998 16.48 11200 0.8077 0.4972
0.1019 17.07 11600 0.8189 0.4921
0.0882 17.66 12000 0.8351 0.4922
0.0855 18.25 12400 0.8688 0.4902
0.0826 18.84 12800 0.8476 0.4916
0.0769 19.43 13200 0.8565 0.4869

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.1+cu118
  • Datasets 1.18.3
  • Tokenizers 0.13.3
Downloads last month
6
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train diallomama/wav2vec2-xls-r-300m-ar

Evaluation results