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NaN grad norm even with a stable loss and gradient

Currently I am working on a custom fine-tune of several code LLMs and while working on the DeepSeekCoder I encountered a strange behaviour. When training the model earlier or later the loss goes to ...
weda's user avatar
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15 views

How can I make my Hugging Face fine-tuned model's config.json file reference a specific revision/commit from the original pretrained model?

I uploaded this model: https://huggingface.co/pamessina/CXRFE, which is a fine-tuned version of this model: https://huggingface.co/microsoft/BiomedVLP-CXR-BERT-specialized Unfortunately, CXR-BERT-...
Pablo Messina's user avatar
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1 answer
38 views

Detection of musical instruments using Yamnet

My goal is to detect musical instruments with AI (machine learning). I'm currently using the Yamnet model to make inferences, but it has a very wide range of categories, for example, "Growling&...
Maxime Dupré's user avatar
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9 views

Validation accuracy dip and recovery when restarting training

i was fine-tuning this large language model with Stochastic Gradient Descent and mid epoch i stopped training, and saved the model weights. Then at a later time, reloaded the weights and restarted the ...
clam's user avatar
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2 votes
1 answer
42 views

Since LoRA parameters are randomly initialized, shouldn't that mean that initially breaks a models output?

I have just tried using LoRA on Llama 3 8B and I found without doing any fine tuning it performed pretty well on my dataset. But then I realized that surely the LoRA parameters are randomly ...
Ameen Izhac's user avatar
1 vote
0 answers
22 views

Train a LLM to learn the entropy of the use case

I want to train a LLM (prefered Llama-2-13b) to learn the entropy of german texts - to be specific sports news. I use perplexity as training metric and want to check the training success after the ...
Christian01's user avatar
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36 views

Fine tuning a model for question-answering task without context on the dataset

I have a small dataset (contains around 2.5k question answer pairs) which I would like to train a T-5 base model on. The code examples that I have came across fine-tune with a dataset which has ...
Nabid Hasan's user avatar
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33 views

How is a causal language model correctly fine-tuned?

I want to fine-tune an SLM like Phi-2 through the huggingface API. I am in doubt how to achieve that, because I see two ways to do that and I am wondering which is the correct way. The task is just a ...
Marcel Braasch's user avatar
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1 answer
37 views

How can I get the list of pretrained large language models?

Is there any place I can get the list of pre-trained large language models in a neat way? Despite the most common ones like gpt, BARD, llama2, which llm do you suggest that can be used for RAG and ...
heyula's user avatar
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1 answer
23 views

How to choose ideal pretrained model for fine-tuning?

I started to work with LLMs lately and want to know how people choose their pre-trained models in their fine-tuning tasks? What is the criteria to choose the base model and which factors affect?
heyula's user avatar
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Can I fine tune MedPaLM model

Is it possible to fine-tune MedPaLM and MedPaLM2; Google's llms trained using PaLM specialized for medical domain. Can we fine-tune these models further to get more specialized models?
heyula's user avatar
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1 vote
1 answer
35 views

Is it methodologically correct to use the data to be used for finetuning in the pretrain phase of the BERT model?

Let us assume the training of a BERT model. An initial pre-train is performed with a large data set A. Subsequently a finetuning is performed with a dataset B which is part of A, but now with labels ...
Álvaro Loza's user avatar
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10 views

Help with a MaNet finetuning (binary semantic segmentation task)

Introduction: I am currently working on a computer vision problem, I have satellite images and I have to detect a particular archeological structure (Tell). I have access to the previously made ...
Alessandro Pistola's user avatar
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24 views

why does my multi-modal model can not learn anything?

I have a multi-modal model. I want to train it using the Pytorch Framework. I have a balanced dataset. I have approximately 150 samples for each client. (I had preprocessed my text data.) when I train ...
arcane_data's user avatar
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1 answer
51 views

Getting a free and unknown answer to a question against a fine-tuned text generation model trained on many essays and their few questions and answers

Aim I want to fine-tune a text generation model with essays of changing size and then ask each of these input texts a few questions. I already have a wider range of question-answer pairs at hand for ...
questionto42's user avatar
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1 answer
174 views

Outdated Transformers TextDataset class drops last block when text overlaps. Replace by datasets Dataset class as input of Trainer train_dataset?

Why I try to replace the transformers TextDataset class with datasets Dataset class I stumbled upon this when I tried to make ...
questionto42's user avatar
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RLHF fine-tune llama2 in vertex ai

I have fine tune RLHF with Vertex AI Pipeline. But deployed model not showing in model registry. Why? code i have used: ...
Sandun Tharaka's user avatar
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2 answers
585 views

How can you get a Huggingface fine-tuning model with the Trainer class from your own text where you can set the arguments for truncation and padding?

I want to find out the role of truncation and padding in Huggingface Transformers pretrained models and any fine-tuning model on top of that. Therefore I played around with these parameters, but I ...
questionto42's user avatar
2 votes
2 answers
1k views

Should you care about truncation and padding in an LLM even if it has a very large tokenizer.max_length so that truncation will never happen?

I want to find out the role of truncation and padding in Huggingface Transformers pretrained models and/or any fine-tuning models on top. Taking a large language model like the German GPT2 shows that ...
questionto42's user avatar
1 vote
0 answers
74 views

Could someone help with fine-tuning dolphin-2.2.1?

Could someone help with fine-tuning dolphin-2.2.1? I have a problem with training: my train\loss - 0 and validation\loss - 0.000... after 800-1000 steps and this is overfitting ...
kabba62's user avatar
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25 views

How to control and optimize optuna

i'm here with a pretty open question. I'm using Optuna to fine tune a Catboost Regressor and i've found, trying a set of parameters by hand, that the "best params" it outputs are not the ...
Alessandro Togni's user avatar
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1 answer
81 views

Fine-tune zero-shot classification model multi-label

I started a small project where I am trying to fine-tune a zero-shot classification model on a proprietary dataset. I was thinking to use the NLI approach, building contradiction and entailment ...
lucatrovato's user avatar
1 vote
0 answers
124 views

Fine-tuning Hugging Face’s Llama Model with Unlabelled Data from PDFs from niche domain

I’m unsure about the next steps. Specifically, I have the following questions: How can I prepare my unlabelled data for the fine-tuning process? What’s the best way to fine-tune the Llama model with ...
Divya Patel's user avatar
2 votes
1 answer
3k views

How to download and fine tune a large language model locally?

I want to fine tune a model locally, not using HuggingFace or any other third party tool. Basically, I want: Download a trained model (Llama-2, Falcon, whatever is easiest). Fine-tune it locally with ...
user's user avatar
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0 votes
0 answers
77 views

Fine-tuning MT5 for making it more like ChatGPT

I am trying to fine-tune a model which works like ChatGPT for Punjabi language, using the mt5-base, however I am not sure if I should go ahead with it since it does not even generate text and when I ...
Rukaiya Hasan's user avatar
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0 answers
29 views

For Finetuning Llama 2, what form of data is required?

I am working on a customer service chatbot project. I have files of different product's manuals on which i need to train the LLM which is Llama 2. As these are manuals so they not in Q/A form. In this ...
divertiss Blogger's user avatar
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0 answers
26 views

TFRobertaSequenceClassification for Address Normalization task

I have dataset with two column: one with faulty addresses, and other with correct addresses. I want to train a model such that, I can use it later for correcting all the incoming faulty addresses. I ...
learner_account's user avatar
1 vote
2 answers
166 views

Training model using BERT

I have generated dataset using chat gpt. Dataset has 9000 data recodes. It's 6 class sentiment analysis. classes are 0,1,2,3,4,5 I used 3000 recodes for training, 1200 recods for validation and ...
Sandun Tharaka's user avatar
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31 views

Is it the right approach to select the model when it gives highest accuracy on validation dataset?

I am training the Densenet121 Model on an image dataset. I divided the dataset into 80% for training and 20% for testing. Then I further divided the training data into 85% for training and 15% for ...
Dawood Ahmad's user avatar
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85 views

Can LLM fine-tuning be used to improve a language?

I'm Danish, and with all the excitement around open LLM models, I'm feeling a little left out. Take Llama 2, for example - it was trained on a very small Danish dataset. Just enough to learn the words ...
mindplay.dk's user avatar
1 vote
0 answers
211 views

How does supervised fine-tuning work in InstructGPT?

See Figure 2 from the InstructGPT paper: I want to know how Step 1 works. Here is one possible algorithm. Pass the prompt through the model, and compute the negative log of the probability of the ...
jskattt797's user avatar
0 votes
1 answer
313 views

Fine-tuning LLM with limited documents and hierarchy

Hello LLM enthusiasts. I am wondering w.r.t. a neighbouring project if there are state of the art approaches to fine tune a model if: the realm of documents is limited (still more than just a few), ...
MaK's user avatar
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292 views

Finetune LLM model on tabular data

Is it possible or even recommended to finetune LLMs such as llama2 on tabular data? I have a csv with historical gold buy prices. ...
fpena06's user avatar
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3 votes
3 answers
9k views

Understanding alpha parameter tuning in LORA paper

I was reading the LORA paper https://arxiv.org/pdf/2106.09685.pdf a thing I don’t understand is section 4.1, where the updates are updated by alpha, where alpha is a constant in r. It is said that ...
jpotwor's user avatar
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0 answers
923 views

Unsupervised fine tuning of Code LLMs

How to prepare code data to fine tune a code LLM in an unsupervised way or is it even possible? For example: Task: Code summarization with custom code base (with no summaries) Let's assume that this ...
Maximos's user avatar
3 votes
1 answer
2k views

LMM Fine Tuning - Supervised Fine Tuning Trainer (SFTTrainer) vs transformers Trainer

When should one opt for the Supervised Fine Tuning Trainer (SFTTrainer) instead of the regular Transformers Trainer when it comes to instruction fine-tuning for Language Models (LLMs)? From what I ...
Marvin Martin's user avatar
0 votes
1 answer
86 views

Can I add a new output class to a decoder and train only the final layer?

I am wondering how to approach a project, where I would like to increase the number of output classes of an already trained network. I have very good reason to believe that the model has already ...
aqua's user avatar
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2 votes
1 answer
1k views

Fine-tuning a pre-trained LLM for question-answering

Objective My goal is to fine-tune a pre-trained LLM on a dataset about Manchester United's (MU's) 2021/22 season (they had a poor season). I want to be able to prompt the fine-tuned model with ...
Tom Bomer's user avatar
0 votes
0 answers
1k views

Easyocr Fine tune english_g2.pth text recognition model using my custom dataset

Am using easy OCR from the link below https://github.com/JaidedAI/EasyOCR I have custom dataset of 25000 images for training and 1000 images for validation in all_data folder generated. Max image ...
K manjunath's user avatar
3 votes
0 answers
2k views

What is zero-shot vs one-short vs few-shot learning?

Are there any papers/research work that deals with generalizing the matrix of how the *-shot(s) learning are defined? There's a wide variety of papers that titled ...
alvas's user avatar
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1 vote
2 answers
87 views

Fine-tune GPT on sketch data (stroke-3)

These past days I have started a personal project where I would like to build a model that, given an uncompleted sketch, it can finish it. I was planning on using some pretrained models that are ...
ilved17's user avatar
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1 vote
1 answer
644 views

How to limit a GPT chatbot in specific domain?

When we are going to fine-tune a GPT-3 model for Q&A in specific domain, how we can avoid it to answer the questions from the other domains? Suppose out chatbot is to answer to questions from ...
Mahdi Amrollahi's user avatar
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0 answers
298 views

How to finetune a closed generative huggingface model?

I want to finetune a huggingface pretrained model on our internal documentation in a way it stats answering related questions. I could not find the adequate tutorial.
welu's user avatar
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2 votes
1 answer
237 views

Does GPT-3 remember data from prompts used to fine tune it?

I am trying to fine tune a model using OpenAI's fine tuning API. I am passing bodies of text (for example, news paper articles) as prompts and the data I want from it as completions. Let us consider ...
Kushal Mohnot's user avatar
2 votes
0 answers
2k views

How many samples in dataset are required to fine-tune BERT for binary classification?

I'm trying to fine-tune a BERT-based model for a binary classification task (data is in English). The dataset I'm working with is quite small (~500 samples, out of which 80% are currently used for ...
Occasus's user avatar
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1 vote
1 answer
197 views

Training a CNN in production on new data

How should I approach training a convolutional neural network in production on new data when I detect model performance degradation due to data or concept drift? Resources like this one and this one ...
Fijoy Vadakkumpadan's user avatar
2 votes
0 answers
585 views

Fine Tune GPT-3 without prompt?

I was wondering if it's possible to fine tune GPT-3 without using the "prompt" and "completion" method as shown in the documentation. More specifically, I want to fine tune a GPT-3 ...
logger22's user avatar
0 votes
1 answer
40 views

About improving the classifier when using a pre-trained model

I have tried adding a layer in the Resnet Model as shown: ...
Hermes Morales's user avatar
1 vote
1 answer
262 views

How to further fine-tune a transformer NLP model on domain specific dataset, after general fine-tuning

I would like to fine-tune a pre-trained BERT-like model for a semantic similarity analysis task in the fashion of the SNLI/MNLI task (i.e. classify sentence pairs to "entailment" or "...
Arthuro's user avatar
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1 vote
1 answer
78 views

Fine tuning Convolutional Neural Network with a learnable first layer

I have a classification task using grayscale images and I want to leverage from pretrained networks. There are a lot of resources out there presenting how to fine tune large neural nets like resnet, ...
nprime496's user avatar