File size: 3,775 Bytes
eb965bb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 |
{
"_name_or_path": "/home/nlp/kleinay/tmp/t5-tst-summarization/qanom/qanom/linearization/permutate_sample_num_of_qas",
"append_verb_form": true,
"architectures": [
"T5ForConditionalGeneration"
],
"d_ff": 2048,
"d_kv": 64,
"d_model": 512,
"debug_mode": false,
"decoder_start_token_id": 0,
"description": "qanom baseline with output_linearization=permutate_sample_num_of_qas, with best hyperparamters for 'by_answer_order' (30ep, accum=8) ",
"dir_switch": "qanom/linearization/permutate_sample_num_of_qas",
"do_eval_on": "validation",
"dropout_rate": 0.15,
"eos_token_id": 1,
"eval_steps": 500,
"evaluation_strategy": "steps",
"feed_forward_proj": "relu",
"fp16": true,
"gradient_accumulation_steps": 8,
"initializer_factor": 1.0,
"is_encoder_decoder": true,
"layer_norm_epsilon": 1e-06,
"learning_rate": 0.001,
"load_best_model_at_end": true,
"logging_steps": 500,
"logging_strategy": "steps",
"metric_for_best_model": "eval_loss",
"model_type": "t5",
"n_positions": 512,
"num_beams": 3,
"num_decoder_layers": 6,
"num_heads": 8,
"num_layers": 6,
"output_past": true,
"overwrite_output_dir": true,
"pad_token_id": 0,
"per_device_eval_batch_size": 12,
"per_device_train_batch_size": 12,
"predicate_marker_type": "generic",
"predict_with_generate": true,
"preprocess_input_func": "input_predicate_marker",
"preprocess_output_func": "permutate_sample_num_of_qas",
"preprocessing_kwargs": {
"append_verb_form": true,
"debug_mode": false,
"description": "qanom baseline with output_linearization=permutate_sample_num_of_qas, with best hyperparamters for 'by_answer_order' (30ep, accum=8) ",
"dir_switch": "qanom/linearization/permutate_sample_num_of_qas",
"do_eval_on": "validation",
"dropout_rate": 0.15,
"eval_steps": 500,
"evaluation_strategy": "steps",
"fp16": true,
"gradient_accumulation_steps": 8,
"learning_rate": 0.001,
"load_best_model_at_end": true,
"logging_steps": 500,
"logging_strategy": "steps",
"metric_for_best_model": "eval_loss",
"model_type": "t5",
"num_beams": 3,
"overwrite_output_dir": true,
"per_device_eval_batch_size": 12,
"per_device_train_batch_size": 12,
"predicate_marker_type": "generic",
"predict_with_generate": true,
"preprocess_input_func": "input_predicate_marker",
"preprocess_output_func": "permutate_sample_num_of_qas",
"qanom_joint_factor": 1,
"save_steps": 500,
"save_strategy": "steps",
"seed": 44,
"source_prefix": "parse: ",
"train_dataset": "qanom",
"train_epochs": 30,
"use_bilateral_predicate_marker": true
},
"qanom_joint_factor": 1,
"relative_attention_num_buckets": 32,
"save_steps": 500,
"save_strategy": "steps",
"seed": 44,
"source_prefix": "parse: ",
"task_specific_params": {
"summarization": {
"early_stopping": true,
"length_penalty": 2.0,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_size": 3,
"num_beams": 4,
"prefix": "summarize: "
},
"translation_en_to_de": {
"early_stopping": true,
"max_length": 300,
"num_beams": 4,
"prefix": "translate English to German: "
},
"translation_en_to_fr": {
"early_stopping": true,
"max_length": 300,
"num_beams": 4,
"prefix": "translate English to French: "
},
"translation_en_to_ro": {
"early_stopping": true,
"max_length": 300,
"num_beams": 4,
"prefix": "translate English to Romanian: "
}
},
"torch_dtype": "float32",
"train_dataset": "qanom",
"train_epochs": 30,
"transformers_version": "4.17.0",
"use_bilateral_predicate_marker": true,
"use_cache": true,
"vocab_size": 32101
}
|