Parameters

• data_path (str) — Path to the dataset.
• model (str) — Name of the model to use. Default is “bert-base-uncased”.
• lr (float) — Learning rate. Default is 5e-5.
• epochs (int) — Number of training epochs. Default is 3.
• max_seq_length (int) — Maximum sequence length. Default is 128.
• batch_size (int) — Training batch size. Default is 8.
• warmup_ratio (float) — Warmup proportion. Default is 0.1.
• gradient_accumulation (int) — Gradient accumulation steps. Default is 1.
• optimizer (str) — Optimizer to use. Default is “adamw_torch”.
• scheduler (str) — Scheduler to use. Default is “linear”.
• weight_decay (float) — Weight decay. Default is 0.0.
• max_grad_norm (float) — Maximum gradient norm. Default is 1.0.
• seed (int) — Random seed. Default is 42.
• train_split (str) — Name of the training split. Default is “train”.
• valid_split (Optional[str]) — Name of the validation split. Default is None.
• tokens_column (str) — Name of the tokens column. Default is “tokens”.
• tags_column (str) — Name of the tags column. Default is “tags”.
• logging_steps (int) — Number of steps between logging. Default is -1.
• project_name (str) — Name of the project. Default is “project-name”.
• auto_find_batch_size (bool) — Whether to automatically find the batch size. Default is False.
• mixed_precision (Optional[str]) — Mixed precision setting (fp16, bf16, or None). Default is None.
• save_total_limit (int) — Total number of checkpoints to save. Default is 1.
• token (Optional[str]) — Hub token for authentication. Default is None.
• push_to_hub (bool) — Whether to push the model to the Hugging Face hub. Default is False.
• eval_strategy (str) — Evaluation strategy. Default is “epoch”.
• username (Optional[str]) — Hugging Face username. Default is None.
• log (str) — Logging method for experiment tracking. Default is “none”.
• early_stopping_patience (int) — Patience for early stopping. Default is 5.
• early_stopping_threshold (float) — Threshold for early stopping. Default is 0.01.