Upload README.md

README.md

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+python run_squad.py   \
+--model_name_or_path google/canine-c  \
+--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-c-squad \
+--model_type bert
+
+{
+  "_name_or_path": "google/canine-c",
+  "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': 58.893093661305585, 'f1': 72.18823344945899}