Register
Login
Resources
Docs Blog Datasets Glossary Case Studies Tutorials & Webinars
Product
Data Engine LLMs Platform Enterprise
Pricing Explore
Connect to our Discord channel
Resources  
Docs Blog Datasets Glossary Case Studies Tutorials & Webinars
Explore Pricing
Product  
Data Engine LLMs Platform Enterprise
Connect to Dagshub Discord channel
Register
Login

avatar mashdud
/
End-to-end-with-MLFLOW
connected to https://github.com/mashdud/End-to-end-with-MLFLOW.git

Watch 1
Issues 0 Pull Requests 0 Discussions 0

running_logs.log 1.8 KB
Permalink History Raw

You have to be logged in to leave a comment. Sign In
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18 
  1. [2024-09-14 00:11:49,748: INFO: comon: yaml file: config\config.yaml loaded successfully]
    2. 

  2. [2024-09-14 00:11:49,755: INFO: comon: yaml file: params.yaml loaded successfully]
    3. 

  3. [2024-09-14 00:11:49,758: INFO: comon: created directory at: artifacts]
    4. 

  4. [2024-09-16 11:23:32,082: INFO: comon: yaml file: config\config.yaml loaded successfully]
    5. 

  5. [2024-09-16 11:23:32,088: INFO: comon: yaml file: params.yaml loaded successfully]
    6. 

  6. [2024-09-16 11:23:32,092: INFO: comon: created directory at: artifacts]
    7. 

  7. [2024-09-16 11:23:32,094: INFO: comon: created directory at: artifacts/prepare_base_model]
    8. 

  8. [2024-09-16 11:23:33,078: WARNING: saving_utils: Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.]
    9. 

  9. [2024-09-16 11:38:50,783: INFO: comon: yaml file: config\config.yaml loaded successfully]
    10. 

  10. [2024-09-16 11:38:50,787: INFO: comon: yaml file: params.yaml loaded successfully]
    11. 

  11. [2024-09-16 11:38:50,789: INFO: comon: created directory at: artifacts]
    12. 

  12. [2024-09-16 11:38:50,791: INFO: comon: created directory at: artifacts/prepare_base_model]
    13. 

  13. [2024-09-16 11:38:51,748: WARNING: saving_utils: Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.]
    14. 

  14. [2024-09-16 11:58:49,591: INFO: comon: yaml file: config\config.yaml loaded successfully]
    15. 

  15. [2024-09-16 11:58:49,599: INFO: comon: yaml file: params.yaml loaded successfully]
    16. 

  16. [2024-09-16 11:58:49,604: INFO: comon: created directory at: artifacts]
    17. 

  17. [2024-09-16 11:58:49,605: INFO: comon: created directory at: artifacts/prepare_base_model]
    18. 

  18. [2024-09-16 11:58:50,262: WARNING: saving_utils: Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.]
    19.
Prev
Next
Tip!

Press p or to see the previous file or, n or to see the next file

Comments

Write Preview
Loading...
Integrate AWS S3
Use S3 remote
Select bucket
Access key
Finish

Use AWS S3 as storage!

Browsing data directories saved to S3 is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your S3 bucket

Access key (If needed)

Congratulations!

End-to-end-with-MLFLOW is now integrated with AWS S3!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes
Integrate Google Cloud Storage
Use Google Storage
Select bucket
Upload key
Finish

Use Google Cloud Storage!

Browsing data directories saved to Google Cloud Storage is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your Google Storage bucket

Service Account Key

Congratulations!

End-to-end-with-MLFLOW is now integrated with Google Cloud Storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes
Integrate Azure Cloud Storage
Use Azure Storage
Select bucket
Set key
Finish

Use Azure Cloud Storage!

Browsing data directories saved to Azure Cloud Storage is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your Azure Storage bucket

Access key (If needed)

Congratulations!

End-to-end-with-MLFLOW is now integrated with Azure Cloud Storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes
Integrate S3 compatible storage
Use S3 like remote
Select bucket
Access key
Finish

Use any S3 compatible storage!

Browsing data directories saved to S3 compatible storage is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your S3 bucket

Bucket name cannot be the same as the repository name. Please change one of them.

Access key (If needed)

Congratulations!

End-to-end-with-MLFLOW is now integrated with your S3 compatible storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes