Datasets:
mteb
/

Modalities:
Tabular
Text
Formats:
json
Libraries:
Datasets
Dask
Muennighoff commited on
Commit
194ddb8
·
verified ·
1 Parent(s): ed99832

Scheduled Commit

Browse files
data/clustering_individual-77467e4a-d00c-437a-8c8c-e7129d54ef5b.jsonl CHANGED
@@ -38,3 +38,8 @@
38
  {"tstamp": 1722291677.7153, "task_type": "clustering", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722291677.6204, "finish": 1722291677.7153, "ip": "", "conv_id": "feaf1621fd304f57b5b3d50f5e85eb75", "model_name": "BAAI/bge-large-en-v1.5", "prompt": ["SGPT: GPT sentence embeddings for semantic search", "MTEB: Massive text embedding benchmark", "C-Pack: Packaged Resources To Advance General Chinese Embedding", "BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval", "Deep Residual Learning for Image Recognition", "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks", "Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
39
  {"tstamp": 1722291721.7903, "task_type": "clustering", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722291721.6928, "finish": 1722291721.7903, "ip": "", "conv_id": "bf31da2ca5b049bd9d082a21e26d8a26", "model_name": "GritLM/GritLM-7B", "prompt": ["SGPT: GPT sentence embeddings for semantic search", "MTEB: Massive text embedding benchmark", "Generative representational instruction tuning", "BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval", "Deep Residual Learning for Image Recognition", "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks", "Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
40
  {"tstamp": 1722291721.7903, "task_type": "clustering", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722291721.6928, "finish": 1722291721.7903, "ip": "", "conv_id": "11d038fb4ecf478fbd8f7d8562325713", "model_name": "BAAI/bge-large-en-v1.5", "prompt": ["SGPT: GPT sentence embeddings for semantic search", "MTEB: Massive text embedding benchmark", "Generative representational instruction tuning", "BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval", "Deep Residual Learning for Image Recognition", "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks", "Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
 
 
 
 
 
 
38
  {"tstamp": 1722291677.7153, "task_type": "clustering", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722291677.6204, "finish": 1722291677.7153, "ip": "", "conv_id": "feaf1621fd304f57b5b3d50f5e85eb75", "model_name": "BAAI/bge-large-en-v1.5", "prompt": ["SGPT: GPT sentence embeddings for semantic search", "MTEB: Massive text embedding benchmark", "C-Pack: Packaged Resources To Advance General Chinese Embedding", "BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval", "Deep Residual Learning for Image Recognition", "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks", "Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
39
  {"tstamp": 1722291721.7903, "task_type": "clustering", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722291721.6928, "finish": 1722291721.7903, "ip": "", "conv_id": "bf31da2ca5b049bd9d082a21e26d8a26", "model_name": "GritLM/GritLM-7B", "prompt": ["SGPT: GPT sentence embeddings for semantic search", "MTEB: Massive text embedding benchmark", "Generative representational instruction tuning", "BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval", "Deep Residual Learning for Image Recognition", "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks", "Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
40
  {"tstamp": 1722291721.7903, "task_type": "clustering", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722291721.6928, "finish": 1722291721.7903, "ip": "", "conv_id": "11d038fb4ecf478fbd8f7d8562325713", "model_name": "BAAI/bge-large-en-v1.5", "prompt": ["SGPT: GPT sentence embeddings for semantic search", "MTEB: Massive text embedding benchmark", "Generative representational instruction tuning", "BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval", "Deep Residual Learning for Image Recognition", "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks", "Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
41
+ {"tstamp": 1722291843.4723, "task_type": "clustering", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722291843.3831, "finish": 1722291843.4723, "ip": "", "conv_id": "72f03b4aecae4106b1a30956e910fc5e", "model_name": "GritLM/GritLM-7B", "prompt": ["MTEB: Massive text embedding benchmark", "BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval", "The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding", "Beyond the imitation game: Quantifying and extrapolating the capabilities of language models", "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks", "Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
42
+ {"tstamp": 1722291843.4723, "task_type": "clustering", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722291843.3831, "finish": 1722291843.4723, "ip": "", "conv_id": "8c887d44d278472aa676f034d8c4736d", "model_name": "BAAI/bge-large-en-v1.5", "prompt": ["MTEB: Massive text embedding benchmark", "BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval", "The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding", "Beyond the imitation game: Quantifying and extrapolating the capabilities of language models", "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks", "Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
43
+ {"tstamp": 1722291915.271, "task_type": "clustering", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722291915.1809, "finish": 1722291915.271, "ip": "", "conv_id": "4dd1657267504ebba4f3a215248029a0", "model_name": "GritLM/GritLM-7B", "prompt": ["MTEB: Massive text embedding benchmark", "BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval", "The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding", "Beyond the imitation game: Quantifying and extrapolating the capabilities of language models", "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks", "Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification", "Deep Residual Learning for Image Recognition"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
44
+ {"tstamp": 1722291915.271, "task_type": "clustering", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722291915.1809, "finish": 1722291915.271, "ip": "", "conv_id": "401f530ea2e64235a906e5e8f9c6b9c5", "model_name": "BAAI/bge-large-en-v1.5", "prompt": ["MTEB: Massive text embedding benchmark", "BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval", "The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding", "Beyond the imitation game: Quantifying and extrapolating the capabilities of language models", "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks", "Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification", "Deep Residual Learning for Image Recognition"], "ncluster": 2, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
45
+ {"tstamp": 1722292121.8444, "task_type": "clustering", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722292121.7878, "finish": 1722292121.8444, "ip": "", "conv_id": "c1a4ede6b5384186851ac40d11025d9a", "model_name": "GritLM/GritLM-7B", "prompt": ["MTEB: Massive text embedding benchmark", "BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval", "The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding", "Beyond the imitation game: Quantifying and extrapolating the capabilities of language models", "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks", "Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification", "Deep Residual Learning for Image Recognition"], "ncluster": 3, "output": "", "ndim": "3D", "dim_method": "PCA", "clustering_method": "KMeans"}