wav2vec2_ljspeech_with_stress

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0431
  • Cer: 0.0073

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: 1000
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Cer
2.9043 1.53 500 3.0446 1.0
1.1195 3.05 1000 0.1302 0.0233
0.1656 4.58 1500 0.0728 0.0149
0.1136 6.11 2000 0.0581 0.0122
0.0852 7.63 2500 0.0508 0.0102
0.0746 9.16 3000 0.0472 0.0093
0.0646 10.69 3500 0.0443 0.0084
0.0588 12.21 4000 0.0442 0.0081
0.0513 13.74 4500 0.0437 0.0077
0.046 15.27 5000 0.0435 0.0075
0.0446 16.79 5500 0.0430 0.0075
0.0429 18.32 6000 0.0433 0.0074
0.0412 19.85 6500 0.0431 0.0072

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.1
Downloads last month
26
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.

Model tree for jz703/wav2vec2_ljspeech_with_stress

Finetuned
(217)
this model