Weights & Biases Reviews & Product Details - Page 3

I first learned about w&b 5 years ago in high school, and used it for a few projects. I now use it every day and have convinced several colleagues in and out of the lab to use w&b. Review collected by and hosted on G2.com.

i wish there was a way to locally/offline view the graphs, or at least be able to view graphs with latency. Review collected by and hosted on G2.com.

I like how it seemlessly integrates into the workflow and reports all relevant information. Review collected by and hosted on G2.com.

I did not like how it remains logged in even without the login command, and how it starts a different log for the same 'run name'. Review collected by and hosted on G2.com.

It is very quick to get started with logging models and performance to wandb, implementation and integration are readily intuitive and straightforward.

There are some useful available features such as model sweeping and other filtering/grouping mechanisms with runs logged in a given project.

Whenever I need to keep track of ML model performance, I use wandb. Review collected by and hosted on G2.com.

The number of concurrent runs is somehow too limited if one launches jobs to a cluster.

It is most of the time hard to find the relevant information you are seeking for in the documentation, hence help comes from issues dealt online by users on different platforms (github, stackoverflow, etc.) Review collected by and hosted on G2.com.

Extremely easy to use (both in browser or via API) + sweep launcher that allows to distributes experiments for different machines Review collected by and hosted on G2.com.

There's no easy pipeline for cross-validation, unless you play a bit around... In any case, it does never get as smooth as the other default functionalities

It is designed for the setting where you have fixed train, val, test sets Review collected by and hosted on G2.com.

Managing runs that are lauched across different machines Review collected by and hosted on G2.com.

All new accounts have to be a team not personal Review collected by and hosted on G2.com.

graphs, experiment logs, easy to share within team Review collected by and hosted on G2.com.

too expensive. latency sometimes sucks too. Review collected by and hosted on G2.com.

i use it as my single point of knowledge for all my experiments results, including model weights, configs, false analysis etc Review collected by and hosted on G2.com.

many specific use cases, which are not that specific imo, i had to implement myself, Review collected by and hosted on G2.com.

W&B is so user-friendly and useful for any ML practitioner but if you are a serious one, you need to get your hands on this tool. Not only you can monitor the performance of your different architecture changes and hyper-parameters, but you can also debug some of the problems with your training. For example, one time I was pulling my hair understanding why my training is so slow, and just by looking at the system dashboard, I realized that CUDA had failed for some reason and I was training on CPU. The system dashboard is also so helpful to find the right batch size to make use of the last MBs of your VRAM, if you know what I mean ;) . All the different plotting options and model/hyper-parameter comparison capabilities, give you a lot of freedom and power to efficiently train machine learning models.

I also appreciate the fact the product is constantly evolving and adapting in flow with the scene of AI. Their blog posts are also a treasure trove of ML knowledge which shows some top-notch serious ML people are working on the product.

All in all, go try it, it is fun and useful! Review collected by and hosted on G2.com.

The UI has a very small delay in updating the progress of your training which you might find annoying if you are an impatient person. Also, I would have loved it if they could add other features like the estimated time to finish the training or even show the time scales of the training steps on the plots (maybe there is a way to activate it but did not find) Review collected by and hosted on G2.com.

Used Weight & Biases for Natural language processing task where i have to train pre-trained models like Bert and RoBerta for classification models. By using Weight & Biases i don't have to manage the weights, loss and accuracy charts. All i have to login and initilize. You can login with your github account. Review collected by and hosted on G2.com.

Honestly nothing, only i think confusion part by viewing different analytics charts get valuable information. Default names mention are also little bit long and confusing. Review collected by and hosted on G2.com.

Very clean and easy to understand UI. Easy integration with Tensorflow, it's nice to see metrics per epoch Review collected by and hosted on G2.com.

Would be nice if there was model deployment functionality. Also, it would be nice to have a service user option or a team API key. Since our runs are triggered using AWS Sagemaker pipelines, we have had to hardcode one of our team member's user API keys which isn't the nicest solution since he isn't always the person triggering the run yet it's still linked to him. Review collected by and hosted on G2.com.