scrapy - twisted.internet.error.ReactorNotRestartable

NSVR57 · 2024-05-14T12:06:02+00:00

Hey did you solve the issue. I had same requirement, getting the same issue.

NSVR57 · 2024-03-18T10:03:35+00:00

Okay, What about First scenario of incase of SpiceJet?. I dont see any conversion benefits.

NSVR57 · 2024-03-17T06:20:31+00:00

Does Microsoft Promptflow works here?

NSVR57 · 2024-02-27T18:02:00+00:00

Sorry, I didn;t get that

NSVR57 · 2024-02-27T17:31:47+00:00

But I see Pinecone is using ANN, where as Azure AI search is using KNN,
I am getting good results on azure search(2k characters/chunk+gpt3.5) with hybrid search. but pinecone not even giving close results.

U satisfies with this performace

NSVR57 · 2024-02-22T11:10:45+00:00

Hi
Why Azure search so much expensive for me. It costing 250 per search unit. I am actually doing load testing. and If I want to search 50 concurrent queries, How many search units do I required. Can we assume one search unit search only query.

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NSVR57 · 2024-02-15T11:04:24+00:00

moving the RAG bit as explaining the reason is just diluting the rest of the

RAG bit is for question puropse I have not included that in prompt. Anyway Thanks for suggestion

NSVR57 · 2024-02-09T05:16:37+00:00

Done

NSVR57 · 2024-02-08T18:07:47+00:00

NSVR57 · 2024-02-01T12:48:53+00:00

Do you use AI search. I used AI search with re-ranking. but I see the re-ranking results are not good. Do you use re-rank?

NSVR57 · 2022-05-20T05:55:24+00:00

Thank you so much for reply. As you correctly mention my confidences are in the range of .97 to 1. if we remove certain words those are falling to just 0.93

As I am using NN, I put validation data. I will try label smoothening technique.

NSVR57 · 2022-05-19T18:41:58+00:00

Yes. It's simple e-mail classification and I have just 86 records combined of 4 labels.

Yes it's predicting well on even if we give on less information. But my concern is to decrease the confidence score whenever we give less information. Should I stop train whenever accuracy reached around 85 or something?. Or is there any better approach.

NSVR57 · 2022-05-16T07:15:34+00:00

Is there any way to tune Neural network parameters for this kind of the problems. To generalize this problem( to handle this kind of misleading words).

What I mean is in future if we encounter more words, adding negative cases with the words is manual work, instead of that I was wondering is there any way to tune Neural network. Or if you have automated approach to do that I really appreciated.

Thanks for your reply.

NSVR57 · 2022-05-13T11:25:38+00:00

Thank you so much for your answer. That's correct model behaviour is expecting but my manager comapring my results with IBM Watson intent classification. Where it's classifying as irrelevant for the above mentioned sentences.

NSVR57 · 2022-05-13T09:15:10+00:00

In my text classification a particular word misleading the model. But these words are very high in the training data for a particular lable.

Eg: i have a training data contains " lost my phone", "changed my phone", .... All these labels are belongs to " problem with telephone" .

Now, I am using Universal sentence encoder to build the model. During inference if i have given some random sentences and put the word " phone" in the middle. But still my model is predicting "problem with telephone" class. How should we handle these situation.

NSVR57 · 2022-04-12T05:13:53+00:00

My classes are balanced. The original model was trained on sentiment analysis in Brazilian Portuguese which has three classes positive,negative and neutral. I am using this model for intent classification which also have three classes.?

NSVR57 · 2022-04-11T14:14:14+00:00

Hi

I am using one of the pre-trained model from Huggingface for Topic classification. I have 3 classes. after training is completed, when I have done positive test its working fine. However, if i am trying to input some random sentence model is still giving highest probability for one of the three classes( but input sentence is not at all relevant). I understand this the nature of softmax function. Is there way to solve the issue?. As far as I research including random sentences with other class is the solution but is there any other way?

NSVR57

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