add model

config.json

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+{
+  "_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
+}

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d678c64d632d4100093eadbce91f9f5dbc9b630c623a0515837cfef9969a0830
+size 242028475