OpenDeltaMirror/examples/examples_text-classification/configs/adapter_roberta-base/cola.json

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{
"bottleneck_dim": 24,
"dataset_config_name": [
"en"
],
"delta_type": "adapter",
"do_eval": true,
"do_test": true,
"do_train": true,
"eval_dataset_config_name": [
"en"
],
"eval_dataset_name": "cola",
"eval_steps": 100,
"evaluation_strategy": "steps",
"greater_is_better": true,
"learning_rate": 0.0003,
"load_best_model_at_end": true,
"max_source_length": 128,
"metric_for_best_model": "eval_accuracy",
"model_name_or_path": "roberta-base",
"num_train_epochs": 20,
"output_dir": "outputs/adapter/roberta-base/cola",
"overwrite_output_dir": true,
"per_device_eval_batch_size": 32,
"per_device_train_batch_size": 32,
"predict_with_generate": true,
"push_to_hub": true,
"save_steps": 100,
"save_strategy": "steps",
"save_total_limit": 1,
"seed": 42,
"task_name": "cola",
"test_dataset_config_name": [
"en"
],
"test_dataset_name": "cola",
"tokenizer_name": "roberta-base",
"unfrozen_modules": [
"deltas",
"layer_norm",
"final_layer_norm",
"classifier"
],
"warmup_steps": 0
}