| exp_name: shona_f5_tts-m150-n150-full-lr1em5-ep30-April-26-2026_02+51PM-b60c1d4 | |
| output_dir: /root/project/runs/shona_f5_tts/shona_f5_tts-m150-n150-full-lr1em5-ep30-April-26-2026_02+51PM-b60c1d4/checkpoints | |
| seed: 42 | |
| model: | |
| type: F5TTS_v1_Base | |
| pretrained: SWivid/F5-TTS | |
| pretrained_ckpt: F5TTS_v1_Base/model_1250000.safetensors | |
| vocab_path: /root/project/datasets/sna-manasseh-150-raw/f5_prepared/default/vocab.txt | |
| use_lora: false | |
| dim: 1024 | |
| depth: 22 | |
| heads: 16 | |
| ff_mult: 2 | |
| text_dim: 512 | |
| conv_layers: 4 | |
| dataset: | |
| name: shona_f5_tts-m150-n150-full-lr1em5-ep30-April-26-2026_02+51PM-b60c1d4 | |
| dir: /root/project/datasets/sna-manasseh-150-raw/f5_prepared/default | |
| metadata: metadata.csv | |
| sample_rate: 24000 | |
| training: | |
| epochs: 30 | |
| learning_rate: 1.0e-05 | |
| weight_decay: 0.01 | |
| max_grad_norm: 1.0 | |
| grad_accumulation_steps: 1 | |
| batch_size_per_gpu: 1600 | |
| batch_size_type: frame | |
| max_samples: 64 | |
| num_warmup_updates: 500 | |
| lr_scheduler: cosine | |
| use_ema: true | |
| ema_decay: 0.9999 | |
| mixed_precision: fp16 | |
| num_workers: 4 | |
| checkpoint: | |
| save_per_updates: 66 | |
| last_per_steps: 10000 | |
| keep_last_n: 5 | |
| logging: | |
| type: wandb | |
| log_per_updates: 50 | |
| wandb_project: f5-tts-shona-finetuning | |
| wandb_run_name: shona_f5_tts-m150-n150-full-lr1em5-ep30-April-26-2026_02+51PM-b60c1d4 | |