excalibur12's picture
Update README.md
2f4f1bc verified
metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - timit_asr
model-index:
  - name: wav2vec2-large_phoneme-timit_english_timit-4k_001
    results: []
language:
  - en
metrics:
  - wer
library_name: transformers
pipeline_tag: automatic-speech-recognition

wav2vec2-large_phoneme-timit_english_timit-4k_001

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

  • Loss: 0.4952
  • Per: 0.1134

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 5000
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Per
4.5458 3.46 1000 0.9087 0.2354
0.7877 6.92 2000 0.4441 0.1506
0.5125 10.38 3000 0.4241 0.1451
0.4485 13.84 4000 0.4244 0.1461
0.4193 17.3 5000 0.4618 0.1510
0.3899 20.76 6000 0.4700 0.1469
0.3244 24.22 7000 0.4496 0.1438
0.2717 27.68 8000 0.4988 0.1455
0.2222 31.14 9000 0.5182 0.1414
0.1872 34.6 10000 0.5320 0.1411

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.1
  • Datasets 2.18.0
  • Tokenizers 0.13.3