This paper refer me to this repo. I don't see any code in this repo. Can you update this repo? Thank you

I see on this website https://grouplens.org/datasets/movielens/ ml-20m.zip is 196MB.

I want to train a next-procedure prediction for the medical dataset. After checking the data processing pipeline, what I have figured out is: the emphasis is done on the sequence of item interaction for users along with the timestamp in the loaded data. But there is no consideration of user features.
But, what I know is user features and item features also play a role, In my case, user features are very critical. How I can use such features to design the sequential recommendation system? Thank you!

Can you upgrade your code to TensorFlow 2.0?

I modified lr=1e-3 (1e-4 in your paper) and found that the convergence speed is much faster. Similar phenomena also appeared in other code reproduction repositories, e.g, cr_1 and cr_2.

my result:
hit@1:0.2399， ndcg@5:0.393, hit@5:0.536, ndcg@10:0.4379=, hit@10:0.6718, ap:0.3794

result from paper:
hit@1:0.3440 ， ndcg@5:0.4967, hit@5:0.6323, ndcg@10:0.5340, hit@10:0.7473, ap:0.4785

Hi, I'm wondering if you also have a PyTorch implementation of the BERT4REC available. Thank you very much!

bert4rec在我们的场景下使用的时候，预测速度非常慢。
这个原因是不是拿了所有物料做softmax导致的。
但是作为cloze任务，这个又无法避免，想问下有什么解决办法吗

I used the original code as well as the ml-1m data listed in the repo. But the loss didn't drop since 10000 iteration, final loss remained on about 5.12. Is there any preprocessing do I need to do before training? Thanks!

any updates for 4 years?
can you share other people git hub repos with different code for session based res sys ?

I'm wondering if you also have a PyTorch implementation of the BERT4REC available. Thank you very much!

After running run_beauty.sh,I got eval_result.txt.
The eval_result.txt only included masked_lm_accuracy and masked_lm_loss.
I tried and found that NDCG and other evaluation metrics only outputed in the info log.
Could you please tell me how can I get these evaluation metrics results and store them in the result txt file?
I found the source codes as followed:
` #tf.logging.info('special eval ops:', special_eval_ops)
result = estimator.evaluate(
input_fn=eval_input_fn,
steps=None,
hooks=[EvalHooks()])

    output_eval_file = os.path.join(FLAGS.checkpointDir,
                                    "eval_results.txt")
    with tf.gfile.GFile(output_eval_file, "w") as writer:
        tf.logging.info("***** Eval results *****")
        tf.logging.info(bert_config.to_json_string())
        writer.write(bert_config.to_json_string()+'\n')
        for key in sorted(result.keys()):
            tf.logging.info("  %s = %s", key, str(result[key]))
            writer.write("%s = %s\n" % (key, str(result[key])))`

The data used in test may exist in the training set.

Hello. Thanks for uploading the code.

But can you also upload how you preprocessed the data?

I would like to reproduce your results from raw data.

Thank you.

Your data generation code is not deterministic, hence making it difficult to reproduce your result.

As shown in the referenced code, create_instances_threading() receive random.Random(random.randint(1, 10000)) as rng, which makes it undeterministic.

Please reply.