wav2vec2-large-lv60_phoneme-timit_english_timit-4k_simplified

• Loss: 0.2796
• Phone Error Rate: 0.0838 (8.38%)

Model description

Intended uses & limitations

Merged Phonemes

• Based on error analysis for each phoneme from the original TIMIT phoneme set.
• See this repo for detailed analysis.
• ax-h → ax
• axr → er
• ix → ih
• ux → uw
• zh → z
• em → m
• en → n
• eng → ng
• nx → n
• hv → hh

Training and evaluation data

Training procedure

Training hyperparameters

• learning_rate: 0.0001
• train_batch_size: 16
• eval_batch_size: 1
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 300
• training_steps: 3000
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.38.1
• Pytorch 2.0.1
• Datasets 2.16.1
• Tokenizers 0.15.2