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Commit
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Librarian Bot: Add language metadata for dataset

Browse files

This pull request aims to enrich the metadata of your dataset by adding language metadata to `YAML` block of your dataset card `README.md`.

How did we find this information?

- The librarian-bot downloaded a sample of rows from your dataset using the [dataset-server](https://huggingface.co/docs/datasets-server/) library
- The librarian-bot used a language detection model to predict the likely language of your dataset. This was done on columns likely to contain text data.
- Predictions for rows are aggregated by language and a filter is applied to remove languages which are very infrequently predicted
- A confidence threshold is applied to remove languages which are not confidently predicted

The following languages were detected with the following mean probabilities:

- English (en): 99.26%


If this PR is merged, the language metadata will be added to your dataset card. This will allow users to filter datasets by language on the [Hub](https://huggingface.co/datasets).
If the language metadata is incorrect, please feel free to close this PR.

To merge this PR, you can use the merge button below the PR:
![Screenshot 2024-02-06 at 15.27.46.png](https://cdn-uploads.huggingface.co/production/uploads/63d3e0e8ff1384ce6c5dd17d/1PRE3CoDpg_wfThC6U1w0.png)

This PR comes courtesy of [Librarian Bot](https://huggingface.co/librarian-bots). If you have any feedback, queries, or need assistance, please don't hesitate to reach out to

@davanstrien
.

Files changed (1) hide show
  1. README.md +73 -33
README.md CHANGED
@@ -1,11 +1,14 @@
1
  ---
 
 
 
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  dataset_info:
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  - config_name: train
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  features:
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- - name: video_path
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  dtype: string
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  - name: internal_id
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- dtype: string
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  - name: prompt
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  dtype: string
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  - name: url
@@ -14,69 +17,111 @@ dataset_info:
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  struct:
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  - name: alignment
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  dtype: int64
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- range: [1,5]
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- - name: composition
 
 
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  dtype: int64
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- range: [1,3]
 
 
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  - name: focus
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  dtype: int64
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- range: [1,3]
 
 
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  - name: camera movement
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  dtype: int64
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- range: [1,3]
 
 
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  - name: color
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  dtype: int64
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- range: [1,5]
 
 
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  - name: lighting accurate
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  dtype: int64
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- range: [1,4]
 
 
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  - name: lighting aes
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  dtype: int64
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- range: [1,5]
 
 
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  - name: shape at beginning
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  dtype: int64
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- range: [0,3]
 
 
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  - name: shape throughout
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  dtype: int64
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- range: [0,4]
 
 
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  - name: object motion dynamic
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  dtype: int64
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- range: [1,5]
 
 
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  - name: camera motion dynamic
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  dtype: int64
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- range: [1,5]
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- - name: movement smoothness
 
 
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  dtype: int64
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- range: [0,4]
 
 
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  - name: movement reality
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  dtype: int64
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- range: [0,4]
 
 
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  - name: clear
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  dtype: int64
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- range: [1,5]
 
 
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  - name: image quality stability
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  dtype: int64
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- range: [1,5]
 
 
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  - name: camera stability
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  dtype: int64
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- range: [1,3]
 
 
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  - name: detail refinement
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  dtype: int64
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- range: [1,5]
 
 
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  - name: letters
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  dtype: int64
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- range: [1,4]
 
 
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  - name: physics law
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  dtype: int64
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- range: [1,5]
 
 
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  - name: unsafe type
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  dtype: int64
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- range: [1,5]
 
 
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  - name: safety
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  dtype: int64
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- range: [1,5]
 
 
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  - name: meta_result
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- sequence:
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  dtype: int64
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  - name: meta_mask
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  sequence:
@@ -84,13 +129,12 @@ dataset_info:
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  splits:
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  - name: train
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  num_examples: 40743
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-
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  - config_name: regression
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  features:
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  - name: internal_id
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  dtype: string
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  - name: prompt
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- dtype: string
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  - name: standard_answer
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  dtype: string
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  - name: video1_path
@@ -100,13 +144,12 @@ dataset_info:
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  splits:
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  - name: regression
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  num_examples: 1795
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-
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  - config_name: test
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  features:
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  - name: internal_id
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  dtype: string
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  - name: prompt
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- dtype: string
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  - name: standard_answer
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  dtype: string
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  - name: video1_path
@@ -116,7 +159,6 @@ dataset_info:
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  splits:
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  - name: test
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  num_examples: 1000
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-
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  configs:
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  - config_name: train
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  data_files:
@@ -130,8 +172,6 @@ configs:
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  data_files:
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  - split: test
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  path: test/*.parquet
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-
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- license: apache-2.0
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  ---
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  # VisionRewardDB-Video
 
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  ---
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+ language:
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+ - en
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+ license: apache-2.0
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  dataset_info:
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  - config_name: train
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  features:
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+ - name: video_path
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  dtype: string
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  - name: internal_id
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+ dtype: string
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  - name: prompt
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  dtype: string
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  - name: url
 
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  struct:
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  - name: alignment
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  dtype: int64
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+ range:
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+ - 1
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+ - 5
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+ - name: composition
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  dtype: int64
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+ range:
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+ - 1
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+ - 3
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  - name: focus
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  dtype: int64
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+ range:
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+ - 1
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+ - 3
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  - name: camera movement
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  dtype: int64
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+ range:
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+ - 1
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+ - 3
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  - name: color
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  dtype: int64
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+ range:
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+ - 1
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+ - 5
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  - name: lighting accurate
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  dtype: int64
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+ range:
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+ - 1
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+ - 4
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  - name: lighting aes
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  dtype: int64
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+ range:
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+ - 1
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+ - 5
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  - name: shape at beginning
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  dtype: int64
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+ range:
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+ - 0
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+ - 3
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  - name: shape throughout
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  dtype: int64
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+ range:
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+ - 0
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+ - 4
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  - name: object motion dynamic
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  dtype: int64
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+ range:
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+ - 1
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+ - 5
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  - name: camera motion dynamic
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  dtype: int64
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+ range:
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+ - 1
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+ - 5
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+ - name: movement smoothness
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  dtype: int64
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+ range:
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+ - 0
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+ - 4
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  - name: movement reality
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  dtype: int64
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+ range:
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+ - 0
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+ - 4
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  - name: clear
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  dtype: int64
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+ range:
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+ - 1
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+ - 5
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  - name: image quality stability
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  dtype: int64
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+ range:
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+ - 1
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+ - 5
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  - name: camera stability
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  dtype: int64
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+ range:
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+ - 1
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+ - 3
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  - name: detail refinement
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  dtype: int64
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+ range:
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+ - 1
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+ - 5
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  - name: letters
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  dtype: int64
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+ range:
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+ - 1
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+ - 4
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  - name: physics law
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  dtype: int64
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+ range:
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+ - 1
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+ - 5
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  - name: unsafe type
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  dtype: int64
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+ range:
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+ - 1
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+ - 5
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  - name: safety
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  dtype: int64
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+ range:
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+ - 1
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+ - 5
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  - name: meta_result
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+ sequence:
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  dtype: int64
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  - name: meta_mask
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  sequence:
 
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  splits:
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  - name: train
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  num_examples: 40743
 
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  - config_name: regression
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  features:
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  - name: internal_id
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  dtype: string
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  - name: prompt
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+ dtype: string
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  - name: standard_answer
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  dtype: string
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  - name: video1_path
 
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  splits:
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  - name: regression
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  num_examples: 1795
 
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  - config_name: test
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  features:
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  - name: internal_id
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  dtype: string
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  - name: prompt
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+ dtype: string
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  - name: standard_answer
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  dtype: string
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  - name: video1_path
 
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  splits:
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  - name: test
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  num_examples: 1000
 
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  configs:
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  - config_name: train
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  data_files:
 
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  data_files:
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  - split: test
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  path: test/*.parquet
 
 
175
  ---
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  # VisionRewardDB-Video