diff --git a/README.md b/README.md index ef89602d2919a0aaac5134519e33b110b7c743e8..e1bd0e0ca79ed0a8be6fec793961b63593d3dfa4 100644 --- a/README.md +++ b/README.md @@ -103,8 +103,8 @@ You can easily re-produce following competitive results with minor codes, which 94.9 94.5 94.7 - 96.3 - 84.0 + 64.3 + 85.2 diff --git a/examples/mrc/README.md b/examples/mrc/README.md index 2f93802ea60b9da8fa5a7b12e757fc42a3d6c990..9d40fd0effbd278a7824aa25f716402eafc5c95c 100644 --- a/examples/mrc/README.md +++ b/examples/mrc/README.md @@ -94,5 +94,5 @@ The evaluation results are as follows: ``` data_num: 3219 -em_sroce: 0.963031997515, f1: 83.9865402973 +em_sroce: 64.3367505436, f1: 85.1781896843 ``` diff --git a/examples/mrc/run.py b/examples/mrc/run.py index 838585073dbbf55ff1703c83441f8fa875fec900..fc3ee79ca1c16d2d574a49a5027eae624085a55b 100644 --- a/examples/mrc/run.py +++ b/examples/mrc/run.py @@ -9,7 +9,7 @@ if __name__ == '__main__': # configs max_seqlen = 512 batch_size = 8 - num_epochs = 8 + num_epochs = 2 lr = 3e-5 doc_stride = 128 max_query_len = 64 @@ -64,8 +64,7 @@ if __name__ == '__main__': # step 8-1*: load pretrained parameters trainer.load_pretrain(pre_params) # step 8-2*: set saver to save model - # save_steps = (n_steps-8) // 4 - save_steps = 1520 + save_steps = 3040 trainer.set_saver(save_path=save_path, save_steps=save_steps, save_type=save_type) # step 8-3: start training trainer.train(print_steps=print_steps) @@ -90,7 +89,7 @@ if __name__ == '__main__': trainer.build_predict_forward(pred_ernie, mrc_pred_head) # step 6: load checkpoint - pred_model_path = './outputs/ckpt.step'+str(12160) + pred_model_path = './outputs/ckpt.step'+str(3040) trainer.load_ckpt(pred_model_path) # step 7: fit prepared reader and data