train_name: local_test
train_id: f
mode: restart
use_deepspeed: true
seed: 44
val_first: false

module_cfg:
  name: m4t_valle

model_cfg:
  model_name: medium
  model_path: /data/pretrained/m4t_m # Change this to the path of the m4t model
  tokenizer_path: /data/pretrained/m4t_m # Change this to the path of the m4t tokenizer
  num_new_tokens: 1025
  use_length_control: true
  codec_path: /data/pretrained/sasc/sasc.pt # Change this to the path of the sasc model



train_dataset_cfg:
  s2st:
    - name: cvss
      data_root: /PATH/TO/CVSSDATASET # Change this to the path of the CVSS dataset
      lang_list:
        - fr
      split: train

val_dataset_cfg:
  - name: cvss
    data_root: /PATH/TO/CVSSDATASET # Change this to the path of the CVSS dataset
    lang_list:
      - fr
    split: test


loader_cfg:
  batch_size: 1
  val_batch_size: 2
  test_batch_size: 1
  num_worker: 2


optim_cfg:
  learning_rate: 2.0e-5
  weight_decay: 0.1
  adam_epsilon: 1.0e-6
  adam_betas: [0.9, 0.98]
  no_decay: ["bias", "layer_norm"]

scheduler_cfg:
  name: poly
  warmup_steps: 10
  lr_end: 1.0e-7
  lr_pow: 1.0

trainer_cfg:
  num_nodes: 1
  max_steps: 300000
  num_sanity_val_steps: 1
  accumulate_grad_batches: 1
  gradient_clip_val: 1.0
  precision: '16-mixed'
  log_every_n_steps: 1
  val_check_interval: 500

ckpt_cfg:
  dirpath: /data/ckpt
  monitor: val_loss
  mode: min
  filename: "ckpt-{epoch:02d}-{val_loss:.2f}"

deepspeed_cfg:
  stage: 0
  offload_optimizer: false
  loss_scale: 0
  min_loss_scale: 0.01















