python run_squad.py --model_name_or_path google/canine-s --do_train --do_eval --per_gpu_train_batch_size 1 --per_gpu_eval_batch_size 1 --gradient_accumulation_steps 128 --learning_rate 3e-5 --num_train_epochs 3 --max_seq_length 1024 --doc_stride 128 --max_answer_length 240 --output_dir canine-s-squad --model_type bert
{ "_name_or_path": "google/canine-s", "architectures": [ "CanineForQuestionAnswering" ], "attention_probs_dropout_prob": 0.1, "bos_token_id": 57344, "downsampling_rate": 4, "eos_token_id": 57345, "hidden_act": "gelu", "hidden_dropout_prob": 0.1, "hidden_size": 768, "initializer_range": 0.02, "intermediate_size": 3072, "layer_norm_eps": 1e-12, "local_transformer_stride": 128, "max_position_embeddings": 16384, "model_type": "canine", "num_attention_heads": 12, "num_hash_buckets": 16384, "num_hash_functions": 8, "num_hidden_layers": 12, "pad_token_id": 0, "torch_dtype": "float32", "transformers_version": "4.19.0.dev0", "type_vocab_size": 16, "upsampling_kernel_size": 4, "use_cache": true }
{'exact': 64.70198675496688, 'f1': 76.57594921776277}
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