Model
NVIDIA Deep Learning Examples
FastPitch checkpoint (PyTorch, AMP, LJSpeech-1.1, 22050Hz)FastPitch PyTorch checkpoint trained on LJSpeech-1.1
21.12.0
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2 Versions
21.12.0Selected03/22/2022 4:50 PM UTC176.57 MBAccuracy: 01500 EpochsBatch Size: 256GPU: V100 Copied!
21.12.0Selected
03/22/2022 4:50 PM UTC176.57 MBAccuracy: 01500 EpochsBatch Size: 256GPU: V100
Copied!
architecture
| Key | Value |
|---|---|
| type | autoaligned; phoneme; pitch conditioning; energy conditioning |
performance
| Key | Value |
|---|---|
| training_loss | 2.68 |
training
| Key | Value |
|---|---|
| batch_size | 256 |
| training_precision | AMP |
| dataset | LJSpeech-1.1 |
| epochs | 1500 |
09/01/2021 12:02 AM UTC176.57 MBAccuracy: 01500 EpochsBatch Size: 256GPU: A100 Copied!
09/01/2021 12:02 AM UTC176.57 MBAccuracy: 01500 EpochsBatch Size: 256GPU: A100
Copied!
architecture
| Key | Value |
|---|---|
| type | autoaligned; phoneme; pitch conditioning; energy conditioning |
performance
| Key | Value |
|---|---|
| training_loss | 2.61 |
training
| Key | Value |
|---|---|
| batch_size | 256 |
| dataset | LJSpeech-1.1 |
| epochs | 1500 |
| training_precision | AMP |