Edit model card

wav2vec2-large-xls-r-300m-kika5_my-colab

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: 0.3860
  • Wer: 0.3505

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: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
4.0007 4.82 400 0.6696 0.8283
0.2774 9.64 800 0.4231 0.5476
0.1182 14.46 1200 0.4253 0.5102
0.0859 19.28 1600 0.4600 0.4866
0.0693 24.1 2000 0.4030 0.4533
0.0611 28.92 2400 0.4189 0.4412
0.0541 33.73 2800 0.4272 0.4380
0.0478 38.55 3200 0.4537 0.4505
0.0428 43.37 3600 0.4349 0.4181
0.038 48.19 4000 0.4562 0.4199
0.0345 53.01 4400 0.4209 0.4310
0.0316 57.83 4800 0.4336 0.4058
0.0288 62.65 5200 0.4004 0.3920
0.025 67.47 5600 0.4115 0.3857
0.0225 72.29 6000 0.4296 0.3948
0.0182 77.11 6400 0.3963 0.3772
0.0165 81.93 6800 0.3921 0.3687
0.0152 86.75 7200 0.3969 0.3592
0.0133 91.57 7600 0.3803 0.3527
0.0118 96.39 8000 0.3860 0.3505

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.10.0+cu111
  • Datasets 1.17.0
  • Tokenizers 0.10.3
Downloads last month
8
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 kika2000/wav2vec2-large-xls-r-300m-kika5_my-colab