jako-xlsr

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the ./SAMPLE_SPEECH.PY - NA dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9486
  • Cer: 0.2606

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: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.03
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Cer
3.5667 1.14 1000 2.2323 0.5188
1.5569 2.28 2000 1.3106 0.3527
1.2238 3.43 3000 1.1109 0.3099
1.0593 4.57 4000 1.0390 0.2891
0.9658 5.71 5000 0.9731 0.2918
0.8796 6.85 6000 0.9479 0.2696
0.8022 8.0 7000 0.9331 0.2710
0.7392 9.14 8000 0.9252 0.2746
0.6694 10.28 9000 0.9318 0.2590
0.5977 11.42 10000 0.9349 0.2674
0.5484 12.56 11000 0.9409 0.2555
0.5154 13.71 12000 0.9510 0.2719
0.4767 14.85 13000 0.9556 0.2624
0.4536 15.99 14000 0.9850 0.2684
0.4195 17.13 15000 0.9894 0.2590
0.3937 18.28 16000 1.0197 0.2698

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.6
  • Tokenizers 0.14.1
Downloads last month
1
Inference Providers NEW
This model is not currently available via any of the supported third-party Inference Providers, and the model is not deployed on the HF Inference API.

Model tree for yesj1234/xlsr_jako_exp2

Finetuned
(229)
this model