Edit model card

k2e-20s_asr-scr_w2v2-base_004

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

  • Loss: 1.6279
  • Per: 0.1742
  • Pcc: 0.5623
  • Ctc Loss: 0.5582
  • Mse Loss: 1.0308

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 1
  • seed: 1234
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2235
  • training_steps: 22350
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Per Pcc Ctc Loss Mse Loss
19.1543 3.0 2235 4.5048 0.9890 0.5904 3.8056 0.7652
4.3704 6.01 4470 4.4024 0.9890 0.5979 3.7604 0.8119
3.8685 9.01 6705 4.2418 0.9890 0.5629 3.5307 0.9394
2.968 12.02 8940 3.0058 0.5972 0.5624 1.9356 1.1595
1.4899 15.02 11175 1.8180 0.2433 0.5595 0.9015 0.9148
0.9431 18.02 13410 1.8391 0.2057 0.5576 0.6985 1.0942
0.7475 21.03 15645 1.6988 0.1896 0.5583 0.6179 1.0382
0.6357 24.03 17880 1.5647 0.1799 0.5494 0.5862 0.9522
0.5695 27.04 20115 1.6835 0.1758 0.5604 0.5648 1.0716
0.5288 30.04 22350 1.6279 0.1742 0.5623 0.5582 1.0308

Framework versions

  • Transformers 4.38.1
  • Pytorch 2.0.1
  • Datasets 2.18.0
  • Tokenizers 0.15.2
Downloads last month
0
Safetensors
Model size
94.6M params
Tensor type
F32
·
Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for excalibur12/k2e-20s_asr-scr_w2v2-base_004

Finetuned
(621)
this model