3.9 KiB
3.9 KiB
MSR-VTT
Overview
MSR-VTT is a large-scale open-domain video captioning benchmark for evaluating video-to-text generation.
The native adapter groups records by video_id, so multiple annotation rows for one video become one sample
with multiple reference captions.
Task Description
- Task Type: Video captioning
- Input: Video clip or URL
- Output: One concise natural-language caption
- Domains: Open-domain video understanding and description
Evaluation Notes
- Default data source:
AI-ModelScope/msr-vtton ModelScope,validationsplit - Hugging Face
VLM2Vec/MSR-VTTremains available by settingextra_params.dataset_hub="huggingface" - Primary metric: CIDEr
- Additional metrics: BLEU-1/2/3/4, METEOR, ROUGE-L
- Set
extra_params.video_dirto prefer local media files over URL metadata
Properties
| Property | Value |
|---|---|
| Benchmark Name | msr_vtt |
| Dataset ID | AI-ModelScope/msr-vtt |
| Paper | Paper |
| Tags | ImageCaptioning, MultiModal |
| Metrics | Bleu_1, Bleu_2, Bleu_3, Bleu_4, METEOR, ROUGE_L, CIDEr |
| Default Shots | 0-shot |
| Evaluation Split | validation |
Data Statistics
| Metric | Value |
|---|---|
| Total Samples | 497 |
| Prompt Length (Mean) | 43 chars |
| Prompt Length (Min/Max) | 43 / 43 chars |
Video Statistics:
| Metric | Value |
|---|---|
| Total Videos | 497 |
| Videos per Sample | min: 1, max: 1, mean: 1 |
| Formats | mp4 |
Sample Example
Subset: default
{
"input": [
{
"id": "36044e4b",
"content": [
{
"text": "Describe the video in one concise sentence."
},
{
"video": "https://www.youtube.com/watch?v=A9pM9iOuAzM",
"format": "mp4",
"start": 116.03,
"end": 126.21
}
]
}
],
"target": "[\"a family is having coversation\"]",
"id": 0,
"group_id": 0,
"metadata": {
"references": [
"a family is having coversation"
],
"subset": "default",
"dataset_id": "AI-ModelScope/msr-vtt",
"dataset_hub": "modelscope",
"video": "https://www.youtube.com/watch?v=A9pM9iOuAzM",
"start": 116.03,
"end": 126.21,
"fps": null,
"video_id": "video6513",
"category": 14
}
}
Prompt Template
Prompt Template:
Describe the video in one concise sentence.
Extra Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
dataset_hub |
str |
modelscope |
Dataset hub used to load MSR-VTT annotations. Choices: ['huggingface', 'modelscope', 'local'] |
eval_split |
str |
`` | Source split to load; defaults to validation for ModelScope and test for Hugging Face. |
dataset_revision |
str |
`` | Optional dataset revision; leave empty to use the hub default. |
video_dir |
str |
`` | Optional local directory containing MSR-VTT video files. |
video_extension |
str |
`` | Optional extension override for local videos, for example "mp4". |
Usage
Using CLI
evalscope eval \
--model YOUR_MODEL \
--api-url OPENAI_API_COMPAT_URL \
--api-key EMPTY_TOKEN \
--datasets msr_vtt \
--limit 10 # Remove this line for formal evaluation
Using Python
from evalscope import run_task
from evalscope.config import TaskConfig
task_cfg = TaskConfig(
model='YOUR_MODEL',
api_url='OPENAI_API_COMPAT_URL',
api_key='EMPTY_TOKEN',
datasets=['msr_vtt'],
dataset_args={
'msr_vtt': {
# extra_params: {} # uses default extra parameters
}
},
limit=10, # Remove this line for formal evaluation
)
run_task(task_cfg=task_cfg)