happy8825/ecva_instruct_ver2_fulltuned
收藏Hugging Face2025-12-19 更新2025-12-20 收录
下载链接：
https://hf-mirror.com/datasets/happy8825/ecva_instruct_ver2_fulltuned
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资源简介：
---
pretty_name: "/hub_data4/seohyun/saves/ecva_instruct/full/sft · happy8825/valid_ecva_clean results"
language:
- en
tags:
- video-retrieval
- evaluation
- vllm
---
# /hub_data4/seohyun/saves/ecva_instruct/full/sft · happy8825/valid_ecva_clean results
- **Model**: `/hub_data4/seohyun/saves/ecva_instruct/full/sft`
- **Dataset**: `happy8825/valid_ecva_clean`
- **Generated**: `2025-12-19 09:18:31Z`
## Metrics
| Metric | Value |
| --- | --- |
| Total samples | 924 |
| With GT | 0 |
| Parsed answers | 0 |
| Top-1 accuracy | 0 |
| Recall@5 | 0 |
| MRR | 0 |
The uploaded JSON contains full per-sample predictions produced via `t3_infer_with_vllm.bash`.
### EVQA/ECVA Metrics
| Metric | Value |
| --- | --- |
| EVQA total | 924 |
| EVQA with GT label | 924 |
| EVQA accuracy | 0.727273 |
## Run Summary
```
Saved 924 results to /home/seohyun/vid_understanding/video_retrieval/video_retrieval/output_ecva_instruct/ecva_instruct_ver2_fulltuned.json
Metrics: {
"total": 924,
"with_gt": 0,
"with_parsed_answer": 0,
"top1_acc": 0.0,
"recall_at_5": 0.0,
"mrr": 0.0,
"num_shards": 1,
"shard_index": 0,
"evqa_total": 924,
"evqa_with_gt_label": 924,
"evqa_acc": 0.7272727272727273
}
Pushed ecva_instruct_ver2_fulltuned.jsonl and README to https://huggingface.co/datasets/happy8825/ecva_instruct_ver2_fulltuned
```
提供机构：
happy8825
