upload the next config
Browse files
README.md
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@@ -139,6 +139,34 @@ dataset_info:
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num_examples: 513
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download_size: 571604579
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dataset_size: 656147207.632
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configs:
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- config_name: matching
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data_files:
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@@ -164,6 +192,14 @@ configs:
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path: ranking/validation-*
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- split: test
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path: ranking/test-*
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---
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# Dataset Card for New Yorker Caption Contest Benchmarks
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num_examples: 513
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download_size: 571604579
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dataset_size: 656147207.632
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- config_name: ranking_from_pixels
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features:
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- name: image
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dtype: image
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- name: contest_number
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dtype: int32
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- name: caption_choices
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sequence: string
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- name: winner_source
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dtype: string
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- name: label
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dtype: string
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- name: n_tokens_label
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dtype: int32
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- name: instance_id
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dtype: string
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splits:
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- name: train
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num_bytes: 101282973.752
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num_examples: 1596
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- name: validation
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num_bytes: 32072331.0
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num_examples: 506
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- name: test
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num_bytes: 28550057.0
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num_examples: 513
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download_size: 134283256
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dataset_size: 161905361.752
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configs:
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- config_name: matching
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data_files:
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path: ranking/validation-*
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- split: test
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path: ranking/test-*
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- config_name: ranking_from_pixels
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data_files:
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- split: train
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path: ranking_from_pixels/train-*
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- split: validation
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path: ranking_from_pixels/validation-*
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- split: test
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path: ranking_from_pixels/test-*
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---
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# Dataset Card for New Yorker Caption Contest Benchmarks
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dataset_infos.json
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"license": "",
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"features": {
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"image": {
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"decode": true,
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"id": null,
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"_type": "Image"
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},
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"contest_number": {
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"dtype": "int32",
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"id": null,
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"_type": "Value"
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},
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"caption_choices": {
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"feature": {
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"dtype": "string",
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"id": null,
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"_type": "Value"
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},
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"length": -1,
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"id": null,
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"_type": "Sequence"
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},
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"winner_source": {
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"dtype": "string",
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"id": null,
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"_type": "Value"
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},
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"label": {
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"dtype": "string",
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"id": null,
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"_type": "Value"
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},
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"n_tokens_label": {
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"dtype": "int32",
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"id": null,
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"_type": "Value"
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},
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"instance_id": {
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"dtype": "string",
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"id": null,
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"_type": "Value"
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}
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},
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"post_processed": null,
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"supervised_keys": null,
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"task_templates": null,
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"builder_name": "newyorker_caption_contest",
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"config_name": "ranking_from_pixels",
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"version": {
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"version_str": "1.0.0",
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"description": null,
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"major": 1,
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"minor": 0,
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"patch": 0
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"splits": {
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"train": {
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"name": "train",
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-
"num_bytes":
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"num_examples": 1596,
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-
"dataset_name":
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},
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"validation": {
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"name": "validation",
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-
"num_bytes":
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"num_examples": 506,
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-
"dataset_name":
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},
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"test": {
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"name": "test",
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"num_bytes":
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"num_examples": 513,
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"dataset_name":
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}
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},
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"download_checksums": {
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"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/huggingface_hub/v1.0/ranking_from_pixels.zip": {
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"num_bytes": 203854,
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"checksum": "6afb6dd49b9558091ce09e4dea0d09a101049bd59ed6d26567cfa3401e60682c"
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},
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"https://storage.googleapis.com/ai2-jack-public/caption_contest_data_public/all_contest_images.zip": {
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"num_bytes": 39523209,
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"checksum": "741527b4ef7198d16cee42ae74eacbe239bcc7377f8b86811c27d627fdc77748"
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}
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},
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-
"download_size":
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"
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"
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"size_in_bytes": 40595794
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},
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"explanation": {
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"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n",
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"license": "",
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"features": {
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"image": {
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"_type": "Image"
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},
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"contest_number": {
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"dtype": "int32",
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"_type": "Value"
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},
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"caption_choices": {
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"feature": {
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"dtype": "string",
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"_type": "Value"
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},
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"_type": "Sequence"
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},
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"winner_source": {
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"dtype": "string",
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"_type": "Value"
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},
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"label": {
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"dtype": "string",
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"_type": "Value"
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},
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"n_tokens_label": {
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"dtype": "int32",
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"_type": "Value"
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},
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"instance_id": {
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"dtype": "string",
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"_type": "Value"
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}
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},
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"builder_name": "newyorker_caption_contest",
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"dataset_name": "newyorker_caption_contest",
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"config_name": "ranking_from_pixels",
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"version": {
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"version_str": "1.0.0",
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"major": 1,
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"minor": 0,
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"patch": 0
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"splits": {
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"train": {
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"name": "train",
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"num_bytes": 101282973.752,
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"num_examples": 1596,
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"dataset_name": null
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},
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"validation": {
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"name": "validation",
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"num_bytes": 32072331.0,
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"num_examples": 506,
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"dataset_name": null
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},
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"test": {
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"name": "test",
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"num_bytes": 28550057.0,
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"num_examples": 513,
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"dataset_name": null
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}
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},
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+
"download_size": 134283256,
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+
"dataset_size": 161905361.752,
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+
"size_in_bytes": 296188617.752
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},
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"explanation": {
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"description": "There are 3 caption contest tasks, described in the paper. In the Matching multiple choice task, models must recognize a caption written about a cartoon (vs. options that were not). In the Quality Ranking task, models must evaluate the quality\nof that caption by scoring it more highly than a lower quality option from the same contest. In the Explanation Generation task, models must explain why the joke is funny.\nYou are given a cartoon and a caption that was written about it. You must autoregressively generate a joke explanation.\n",
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ranking_from_pixels/test-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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size 20554836
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ranking_from_pixels/train-00000-of-00001.parquet
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ranking_from_pixels/validation-00000-of-00001.parquet
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