wav2vec2-stt / README.md
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metadata
language:
  - eng
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
  - '[finetuned_model, lj_speech11]'
  - generated_from_trainer
datasets:
  - FYP/LJ-SpeechLJ
metrics:
  - wer
model-index:
  - name: SpeechT5 STT Wav2Vec2
    results: []

SpeechT5 STT Wav2Vec2

This model is a fine-tuned version of facebook/wav2vec2-base-960h on the Lj-Speech dataset. It achieves the following results on the evaluation set:

  • Loss: 252.7729
  • Wer: 1.0

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: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
130.9264 0.5319 50 256.5228 0.9827
134.1007 1.0638 100 256.2832 0.9827
131.0841 1.5957 150 253.9561 0.9827
132.4283 2.1277 200 254.4677 0.9827
137.3693 2.6596 250 254.6855 1.0
128.1369 3.1915 300 252.8348 1.0
132.3826 3.7234 350 254.7122 1.0
130.9401 4.2553 400 254.6629 1.0
129.5693 4.7872 450 252.7729 1.0

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1