metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-lv60
tags:
- generated_from_trainer
- phoneme-recognition
model-index:
- name: wav2vec2-large-lv60_phoneme-timit_english_timit-4k
results:
- task:
type: phoneme-recognition
name: Phoneme Recognition
dataset:
name: TIMIT
type: timit-asr/timit_asr
split: test
args: full phoneme set
metrics:
- name: Phone Error Rate
type: per
value: 0.1053
datasets:
- timit-asr/timit_asr
language:
- en
metrics:
- per
library_name: transformers
wav2vec2-large-lv60_phoneme-timit_english_timit-4k
This model is a fine-tuned version of facebook/wav2vec2-large-lv60 on the TIMIT dataset. It achieves the following results on the evaluation set:
- Loss: 0.3354
- Phone Error Rate: 0.1053 (10.53%)
Intended uses & limitations
- Phoneme recognition based on the TIMIT phoneme set
Phoneme-wise errors
Vowel Phonemes
Stop Phonemes
Affricate Phonemes
Fricative Phonemes
Nasal Phonemes
Semivowels/Glide Phonemes
Training and evaluation data
- Train: TIMIT train dataset (4620 samples)
- Test: TIMIT test dataset (1680 samples)
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- 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
| Training Loss | Epoch | Step | Validation Loss | PER |
|---|---|---|---|---|
| 7.9352 | 1.04 | 300 | 3.7710 | 0.9617 |
| 2.7874 | 2.08 | 600 | 0.9080 | 0.1929 |
| 0.8205 | 3.11 | 900 | 0.4670 | 0.1492 |
| 0.5504 | 4.15 | 1200 | 0.4025 | 0.1408 |
| 0.4632 | 5.19 | 1500 | 0.3696 | 0.1374 |
| 0.4148 | 6.23 | 1800 | 0.3519 | 0.1343 |
| 0.3873 | 7.27 | 2100 | 0.3419 | 0.1329 |
| 0.3695 | 8.3 | 2400 | 0.3368 | 0.1317 |
| 0.3531 | 9.34 | 2700 | 0.3406 | 0.1320 |
| 0.3507 | 10.38 | 3000 | 0.3354 | 0.1315 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.2