E5 (code, models, paper)
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- .gitattributes +1 -0
- Text Embeddings by Weakly-Supervised Contrastive Pre-training.pdf +3 -0
- e5-base-v2/.gitattributes +35 -0
- e5-base-v2/README.md +24 -0
- e5-base-v2/config.json +25 -0
- e5-base-v2/onnx/model.onnx +3 -0
- e5-base-v2/onnx/model_bnb4.onnx +3 -0
- e5-base-v2/onnx/model_fp16.onnx +3 -0
- e5-base-v2/onnx/model_int8.onnx +3 -0
- e5-base-v2/onnx/model_q4.onnx +3 -0
- e5-base-v2/onnx/model_q4f16.onnx +3 -0
- e5-base-v2/onnx/model_quantized.onnx +3 -0
- e5-base-v2/onnx/model_uint8.onnx +3 -0
- e5-base-v2/quant_config.json +30 -0
- e5-base-v2/source.txt +1 -0
- e5-base-v2/special_tokens_map.json +7 -0
- e5-base-v2/tokenizer.json +0 -0
- e5-base-v2/tokenizer_config.json +13 -0
- e5-base-v2/vocab.txt +0 -0
- e5-small-Quran/.gitattributes +34 -0
- e5-small-Quran/README.md +41 -0
- e5-small-Quran/config.json +25 -0
- e5-small-Quran/pytorch_model.bin +3 -0
- e5-small-Quran/source.txt +1 -0
- e5-small-Quran/special_tokens_map.json +7 -0
- e5-small-Quran/tokenizer.json +0 -0
- e5-small-Quran/tokenizer_config.json +15 -0
- e5-small-Quran/vocab.txt +0 -0
- e5-small-v2-quantized/.gitattributes +35 -0
- e5-small-v2-quantized/README.md +3 -0
- e5-small-v2-quantized/config.json +24 -0
- e5-small-v2-quantized/onnx/model.onnx +3 -0
- e5-small-v2-quantized/onnx/model_quantized.onnx +3 -0
- e5-small-v2-quantized/quantize_config.json +30 -0
- e5-small-v2-quantized/source.txt +1 -0
- e5-small-v2-quantized/special_tokens_map.json +7 -0
- e5-small-v2-quantized/tokenizer.json +0 -0
- e5-small-v2-quantized/tokenizer_config.json +15 -0
- e5-small-v2-quantized/vocab.txt +0 -0
- e5-small-v2/.gitattributes +34 -0
- e5-small-v2/1_Pooling/config.json +7 -0
- e5-small-v2/README.md +2686 -0
- e5-small-v2/config.json +25 -0
- e5-small-v2/modules.json +20 -0
- e5-small-v2/pytorch_model.bin +3 -0
- e5-small-v2/sentence_bert_config.json +4 -0
- e5-small-v2/source.txt +1 -0
- e5-small-v2/special_tokens_map.json +7 -0
- e5-small-v2/tokenizer.json +0 -0
- e5-small-v2/tokenizer_config.json +15 -0
.gitattributes
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Text[[:space:]]Embeddings[[:space:]]by[[:space:]]Weakly-Supervised[[:space:]]Contrastive[[:space:]]Pre-training.pdf filter=lfs diff=lfs merge=lfs -text
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Text Embeddings by Weakly-Supervised Contrastive Pre-training.pdf
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e5-base-v2/.gitattributes
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*.onnx filter=lfs diff=lfs merge=lfs -text
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*.safetensors filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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e5-base-v2/README.md
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---
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base_model: intfloat/e5-base-v2
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library_name: transformers.js
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---
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https://huggingface.co/intfloat/e5-base-v2 with ONNX weights to be compatible with Transformers.js.
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## Usage (Transformers.js)
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If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@huggingface/transformers) using:
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```bash
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npm i @huggingface/transformers
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```
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**Example:** Run feature extraction.
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```js
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import { pipeline } from '@huggingface/transformers';
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const extractor = await pipeline('feature-extraction', 'Xenova/e5-base-v2');
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const output = await extractor('This is a simple test.');
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```
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Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using [🤗 Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).
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e5-base-v2/config.json
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{
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"_name_or_path": "intfloat/e5-base-v2",
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"architectures": [
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"BertModel"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"transformers_version": "4.30.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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e5-base-v2/onnx/model.onnx
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size 435811516
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e5-base-v2/onnx/model_bnb4.onnx
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version https://git-lfs.github.com/spec/v1
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e5-base-v2/onnx/model_fp16.onnx
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e5-base-v2/onnx/model_int8.onnx
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e5-base-v2/onnx/model_q4.onnx
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version https://git-lfs.github.com/spec/v1
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e5-base-v2/onnx/model_q4f16.onnx
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version https://git-lfs.github.com/spec/v1
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e5-base-v2/onnx/model_quantized.onnx
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version https://git-lfs.github.com/spec/v1
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e5-base-v2/onnx/model_uint8.onnx
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version https://git-lfs.github.com/spec/v1
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e5-base-v2/quant_config.json
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{
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"per_channel": true,
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"reduce_range": true,
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"per_model_config": {
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"model": {
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"op_types": [
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"Concat",
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"Shape",
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"Erf",
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"Mul",
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"Reshape",
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"Pow",
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"Sqrt",
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"ReduceMean",
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"Gather",
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"Div",
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"Cast",
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"Transpose",
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"Softmax",
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"Slice",
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"MatMul",
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"Constant",
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"Unsqueeze",
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"Add",
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"Sub"
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],
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"weight_type": "QInt8"
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}
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}
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}
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e5-base-v2/source.txt
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https://huggingface.co/Xenova/e5-base-v2
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e5-base-v2/special_tokens_map.json
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{
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"cls_token": "[CLS]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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e5-base-v2/tokenizer.json
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e5-base-v2/tokenizer_config.json
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{
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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e5-base-v2/vocab.txt
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e5-small-Quran/.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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*.bin filter=lfs diff=lfs merge=lfs -text
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*.ckpt filter=lfs diff=lfs merge=lfs -text
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*.ftz filter=lfs diff=lfs merge=lfs -text
|
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*.gz filter=lfs diff=lfs merge=lfs -text
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*.h5 filter=lfs diff=lfs merge=lfs -text
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| 9 |
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*.joblib filter=lfs diff=lfs merge=lfs -text
|
| 10 |
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*.lfs.* filter=lfs diff=lfs merge=lfs -text
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*.mlmodel filter=lfs diff=lfs merge=lfs -text
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*.model filter=lfs diff=lfs merge=lfs -text
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*.msgpack filter=lfs diff=lfs merge=lfs -text
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*.npy filter=lfs diff=lfs merge=lfs -text
|
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*.npz filter=lfs diff=lfs merge=lfs -text
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*.onnx filter=lfs diff=lfs merge=lfs -text
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| 17 |
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*.ot filter=lfs diff=lfs merge=lfs -text
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| 18 |
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*.parquet filter=lfs diff=lfs merge=lfs -text
|
| 19 |
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*.pb filter=lfs diff=lfs merge=lfs -text
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| 20 |
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*.pickle filter=lfs diff=lfs merge=lfs -text
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| 21 |
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*.pkl filter=lfs diff=lfs merge=lfs -text
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| 22 |
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*.pt filter=lfs diff=lfs merge=lfs -text
|
| 23 |
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*.pth filter=lfs diff=lfs merge=lfs -text
|
| 24 |
+
*.rar filter=lfs diff=lfs merge=lfs -text
|
| 25 |
+
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
| 26 |
+
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
| 27 |
+
*.tar.* filter=lfs diff=lfs merge=lfs -text
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| 28 |
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*.tflite filter=lfs diff=lfs merge=lfs -text
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| 29 |
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*.tgz filter=lfs diff=lfs merge=lfs -text
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*.wasm filter=lfs diff=lfs merge=lfs -text
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*.xz filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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| 33 |
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*.zst filter=lfs diff=lfs merge=lfs -text
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| 34 |
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*tfevents* filter=lfs diff=lfs merge=lfs -text
|
e5-small-Quran/README.md
ADDED
|
@@ -0,0 +1,41 @@
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|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
datasets:
|
| 4 |
+
- M-AI-C/quran-en-tafssirs
|
| 5 |
+
language:
|
| 6 |
+
- en
|
| 7 |
+
---
|
| 8 |
+
```python
|
| 9 |
+
import torch.nn.functional as F
|
| 10 |
+
|
| 11 |
+
from torch import Tensor
|
| 12 |
+
from transformers import AutoTokenizer, AutoModel
|
| 13 |
+
|
| 14 |
+
|
| 15 |
+
def average_pool(last_hidden_states: Tensor,
|
| 16 |
+
attention_mask: Tensor) -> Tensor:
|
| 17 |
+
last_hidden = last_hidden_states.masked_fill(~attention_mask[..., None].bool(), 0.0)
|
| 18 |
+
return last_hidden.sum(dim=1) / attention_mask.sum(dim=1)[..., None]
|
| 19 |
+
|
| 20 |
+
|
| 21 |
+
# Each input text should start with "query: " or "passage: ".
|
| 22 |
+
# For tasks other than retrieval, you can simply use the "query: " prefix.
|
| 23 |
+
input_texts = ['query: Who is prophet known for patience',
|
| 24 |
+
'query: Who is moses',
|
| 25 |
+
"passage: passage 1",
|
| 26 |
+
"passage: passage 2"]
|
| 27 |
+
|
| 28 |
+
tokenizer = AutoTokenizer.from_pretrained('intfloat/e5-small')
|
| 29 |
+
model = AutoModel.from_pretrained('intfloat/e5-small')
|
| 30 |
+
|
| 31 |
+
# Tokenize the input texts
|
| 32 |
+
batch_dict = tokenizer(input_texts, max_length=512, padding=True, truncation=True, return_tensors='pt')
|
| 33 |
+
|
| 34 |
+
outputs = model(**batch_dict)
|
| 35 |
+
embeddings = average_pool(outputs.last_hidden_state, batch_dict['attention_mask'])
|
| 36 |
+
|
| 37 |
+
# (Optionally) normalize embeddings
|
| 38 |
+
embeddings = F.normalize(embeddings, p=2, dim=1)
|
| 39 |
+
scores = (embeddings[:2] @ embeddings[2:].T) * 100
|
| 40 |
+
print(scores.tolist())
|
| 41 |
+
```
|
e5-small-Quran/config.json
ADDED
|
@@ -0,0 +1,25 @@
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|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "intfloat/e5-small",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"BertModel"
|
| 5 |
+
],
|
| 6 |
+
"attention_probs_dropout_prob": 0.1,
|
| 7 |
+
"classifier_dropout": null,
|
| 8 |
+
"hidden_act": "gelu",
|
| 9 |
+
"hidden_dropout_prob": 0.1,
|
| 10 |
+
"hidden_size": 384,
|
| 11 |
+
"initializer_range": 0.02,
|
| 12 |
+
"intermediate_size": 1536,
|
| 13 |
+
"layer_norm_eps": 1e-12,
|
| 14 |
+
"max_position_embeddings": 512,
|
| 15 |
+
"model_type": "bert",
|
| 16 |
+
"num_attention_heads": 12,
|
| 17 |
+
"num_hidden_layers": 12,
|
| 18 |
+
"pad_token_id": 0,
|
| 19 |
+
"position_embedding_type": "absolute",
|
| 20 |
+
"torch_dtype": "float32",
|
| 21 |
+
"transformers_version": "4.27.4",
|
| 22 |
+
"type_vocab_size": 2,
|
| 23 |
+
"use_cache": true,
|
| 24 |
+
"vocab_size": 30522
|
| 25 |
+
}
|
e5-small-Quran/pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:fad09317c5f9b844024d0b4219bf4e006dc5a7a958079b18cb3300d363d0f4d6
|
| 3 |
+
size 133511213
|
e5-small-Quran/source.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
https://huggingface.co/mustapha/e5-small-Quran
|
e5-small-Quran/special_tokens_map.json
ADDED
|
@@ -0,0 +1,7 @@
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|
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|
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|
|
|
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|
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|
|
|
|
| 1 |
+
{
|
| 2 |
+
"cls_token": "[CLS]",
|
| 3 |
+
"mask_token": "[MASK]",
|
| 4 |
+
"pad_token": "[PAD]",
|
| 5 |
+
"sep_token": "[SEP]",
|
| 6 |
+
"unk_token": "[UNK]"
|
| 7 |
+
}
|
e5-small-Quran/tokenizer.json
ADDED
|
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|
|
e5-small-Quran/tokenizer_config.json
ADDED
|
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|
| 1 |
+
{
|
| 2 |
+
"cls_token": "[CLS]",
|
| 3 |
+
"do_basic_tokenize": true,
|
| 4 |
+
"do_lower_case": true,
|
| 5 |
+
"mask_token": "[MASK]",
|
| 6 |
+
"model_max_length": 1000000000000000019884624838656,
|
| 7 |
+
"never_split": null,
|
| 8 |
+
"pad_token": "[PAD]",
|
| 9 |
+
"sep_token": "[SEP]",
|
| 10 |
+
"special_tokens_map_file": null,
|
| 11 |
+
"strip_accents": null,
|
| 12 |
+
"tokenize_chinese_chars": true,
|
| 13 |
+
"tokenizer_class": "BertTokenizer",
|
| 14 |
+
"unk_token": "[UNK]"
|
| 15 |
+
}
|
e5-small-Quran/vocab.txt
ADDED
|
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|
|
|
e5-small-v2-quantized/.gitattributes
ADDED
|
@@ -0,0 +1,35 @@
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|
| 1 |
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*.7z filter=lfs diff=lfs merge=lfs -text
|
| 2 |
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*.arrow filter=lfs diff=lfs merge=lfs -text
|
| 3 |
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*.bin filter=lfs diff=lfs merge=lfs -text
|
| 4 |
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*.bz2 filter=lfs diff=lfs merge=lfs -text
|
| 5 |
+
*.ckpt filter=lfs diff=lfs merge=lfs -text
|
| 6 |
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*.ftz filter=lfs diff=lfs merge=lfs -text
|
| 7 |
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*.gz filter=lfs diff=lfs merge=lfs -text
|
| 8 |
+
*.h5 filter=lfs diff=lfs merge=lfs -text
|
| 9 |
+
*.joblib filter=lfs diff=lfs merge=lfs -text
|
| 10 |
+
*.lfs.* filter=lfs diff=lfs merge=lfs -text
|
| 11 |
+
*.mlmodel filter=lfs diff=lfs merge=lfs -text
|
| 12 |
+
*.model filter=lfs diff=lfs merge=lfs -text
|
| 13 |
+
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
| 14 |
+
*.npy filter=lfs diff=lfs merge=lfs -text
|
| 15 |
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*.npz filter=lfs diff=lfs merge=lfs -text
|
| 16 |
+
*.onnx filter=lfs diff=lfs merge=lfs -text
|
| 17 |
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*.ot filter=lfs diff=lfs merge=lfs -text
|
| 18 |
+
*.parquet filter=lfs diff=lfs merge=lfs -text
|
| 19 |
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*.pb filter=lfs diff=lfs merge=lfs -text
|
| 20 |
+
*.pickle filter=lfs diff=lfs merge=lfs -text
|
| 21 |
+
*.pkl filter=lfs diff=lfs merge=lfs -text
|
| 22 |
+
*.pt filter=lfs diff=lfs merge=lfs -text
|
| 23 |
+
*.pth filter=lfs diff=lfs merge=lfs -text
|
| 24 |
+
*.rar filter=lfs diff=lfs merge=lfs -text
|
| 25 |
+
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
| 26 |
+
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
| 27 |
+
*.tar.* filter=lfs diff=lfs merge=lfs -text
|
| 28 |
+
*.tar filter=lfs diff=lfs merge=lfs -text
|
| 29 |
+
*.tflite filter=lfs diff=lfs merge=lfs -text
|
| 30 |
+
*.tgz filter=lfs diff=lfs merge=lfs -text
|
| 31 |
+
*.wasm filter=lfs diff=lfs merge=lfs -text
|
| 32 |
+
*.xz filter=lfs diff=lfs merge=lfs -text
|
| 33 |
+
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
+
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
+
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
e5-small-v2-quantized/README.md
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
---
|
e5-small-v2-quantized/config.json
ADDED
|
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "ggrn/e5-small-v2",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"BertModel"
|
| 5 |
+
],
|
| 6 |
+
"attention_probs_dropout_prob": 0.1,
|
| 7 |
+
"classifier_dropout": null,
|
| 8 |
+
"hidden_act": "gelu",
|
| 9 |
+
"hidden_dropout_prob": 0.1,
|
| 10 |
+
"hidden_size": 384,
|
| 11 |
+
"initializer_range": 0.02,
|
| 12 |
+
"intermediate_size": 1536,
|
| 13 |
+
"layer_norm_eps": 1e-12,
|
| 14 |
+
"max_position_embeddings": 512,
|
| 15 |
+
"model_type": "bert",
|
| 16 |
+
"num_attention_heads": 12,
|
| 17 |
+
"num_hidden_layers": 12,
|
| 18 |
+
"pad_token_id": 0,
|
| 19 |
+
"position_embedding_type": "absolute",
|
| 20 |
+
"transformers_version": "4.31.0.dev0",
|
| 21 |
+
"type_vocab_size": 2,
|
| 22 |
+
"use_cache": true,
|
| 23 |
+
"vocab_size": 30522
|
| 24 |
+
}
|
e5-small-v2-quantized/onnx/model.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:20a0dbefd78b3e8a62955c0c95650907d7a0b8ccb5e1b052ce3e26c54900233b
|
| 3 |
+
size 133093490
|
e5-small-v2-quantized/onnx/model_quantized.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c5bb8cbf8f1c2ab993e6385918e202d746d7678a10d50dfaae74b2086ea282b0
|
| 3 |
+
size 34014426
|
e5-small-v2-quantized/quantize_config.json
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
| 1 |
+
{
|
| 2 |
+
"per_channel": true,
|
| 3 |
+
"reduce_range": true,
|
| 4 |
+
"per_model_config": {
|
| 5 |
+
"model": {
|
| 6 |
+
"op_types": [
|
| 7 |
+
"Cast",
|
| 8 |
+
"Concat",
|
| 9 |
+
"Add",
|
| 10 |
+
"Constant",
|
| 11 |
+
"Div",
|
| 12 |
+
"ReduceMean",
|
| 13 |
+
"Softmax",
|
| 14 |
+
"Erf",
|
| 15 |
+
"Unsqueeze",
|
| 16 |
+
"Transpose",
|
| 17 |
+
"Slice",
|
| 18 |
+
"Shape",
|
| 19 |
+
"MatMul",
|
| 20 |
+
"Pow",
|
| 21 |
+
"Sub",
|
| 22 |
+
"Sqrt",
|
| 23 |
+
"Reshape",
|
| 24 |
+
"Gather",
|
| 25 |
+
"Mul"
|
| 26 |
+
],
|
| 27 |
+
"weight_type": "QInt8"
|
| 28 |
+
}
|
| 29 |
+
}
|
| 30 |
+
}
|
e5-small-v2-quantized/source.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
https://huggingface.co/ankitgupta8768/e5-small-v2-quantized
|
e5-small-v2-quantized/special_tokens_map.json
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"cls_token": "[CLS]",
|
| 3 |
+
"mask_token": "[MASK]",
|
| 4 |
+
"pad_token": "[PAD]",
|
| 5 |
+
"sep_token": "[SEP]",
|
| 6 |
+
"unk_token": "[UNK]"
|
| 7 |
+
}
|
e5-small-v2-quantized/tokenizer.json
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|
e5-small-v2-quantized/tokenizer_config.json
ADDED
|
@@ -0,0 +1,15 @@
|
|
|
|
|
|
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|
| 1 |
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{
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| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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"do_lower_case": true,
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| 6 |
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| 7 |
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| 8 |
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| 10 |
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| 11 |
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| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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e5-small-v2-quantized/vocab.txt
ADDED
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|
|
e5-small-v2/.gitattributes
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| 9 |
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| 10 |
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| 12 |
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| 18 |
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| 19 |
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| 20 |
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| 21 |
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| 22 |
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| 23 |
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| 24 |
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| 25 |
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| 26 |
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|
| 27 |
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| 28 |
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| 29 |
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| 30 |
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| 31 |
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| 32 |
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| 33 |
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|
| 34 |
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|
e5-small-v2/1_Pooling/config.json
ADDED
|
@@ -0,0 +1,7 @@
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|
| 6 |
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|
| 7 |
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}
|
e5-small-v2/README.md
ADDED
|
@@ -0,0 +1,2686 @@
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|
| 1 |
+
---
|
| 2 |
+
language:
|
| 3 |
+
- en
|
| 4 |
+
license: mit
|
| 5 |
+
library_name: sentence-transformers
|
| 6 |
+
pipeline_tag: feature-extraction
|
| 7 |
+
tags:
|
| 8 |
+
- mteb
|
| 9 |
+
model-index:
|
| 10 |
+
- name: e5-small-v2
|
| 11 |
+
results:
|
| 12 |
+
- task:
|
| 13 |
+
type: Classification
|
| 14 |
+
dataset:
|
| 15 |
+
type: mteb/amazon_counterfactual
|
| 16 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
| 17 |
+
config: en
|
| 18 |
+
split: test
|
| 19 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
| 20 |
+
metrics:
|
| 21 |
+
- type: accuracy
|
| 22 |
+
value: 77.59701492537313
|
| 23 |
+
- type: ap
|
| 24 |
+
value: 41.67064885731708
|
| 25 |
+
- type: f1
|
| 26 |
+
value: 71.86465946398573
|
| 27 |
+
- task:
|
| 28 |
+
type: Classification
|
| 29 |
+
dataset:
|
| 30 |
+
type: mteb/amazon_polarity
|
| 31 |
+
name: MTEB AmazonPolarityClassification
|
| 32 |
+
config: default
|
| 33 |
+
split: test
|
| 34 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
| 35 |
+
metrics:
|
| 36 |
+
- type: accuracy
|
| 37 |
+
value: 91.265875
|
| 38 |
+
- type: ap
|
| 39 |
+
value: 87.67633085349644
|
| 40 |
+
- type: f1
|
| 41 |
+
value: 91.24297521425744
|
| 42 |
+
- task:
|
| 43 |
+
type: Classification
|
| 44 |
+
dataset:
|
| 45 |
+
type: mteb/amazon_reviews_multi
|
| 46 |
+
name: MTEB AmazonReviewsClassification (en)
|
| 47 |
+
config: en
|
| 48 |
+
split: test
|
| 49 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
| 50 |
+
metrics:
|
| 51 |
+
- type: accuracy
|
| 52 |
+
value: 45.882000000000005
|
| 53 |
+
- type: f1
|
| 54 |
+
value: 45.08058870381236
|
| 55 |
+
- task:
|
| 56 |
+
type: Retrieval
|
| 57 |
+
dataset:
|
| 58 |
+
type: arguana
|
| 59 |
+
name: MTEB ArguAna
|
| 60 |
+
config: default
|
| 61 |
+
split: test
|
| 62 |
+
revision: None
|
| 63 |
+
metrics:
|
| 64 |
+
- type: map_at_1
|
| 65 |
+
value: 20.697
|
| 66 |
+
- type: map_at_10
|
| 67 |
+
value: 33.975
|
| 68 |
+
- type: map_at_100
|
| 69 |
+
value: 35.223
|
| 70 |
+
- type: map_at_1000
|
| 71 |
+
value: 35.260000000000005
|
| 72 |
+
- type: map_at_3
|
| 73 |
+
value: 29.776999999999997
|
| 74 |
+
- type: map_at_5
|
| 75 |
+
value: 32.035000000000004
|
| 76 |
+
- type: mrr_at_1
|
| 77 |
+
value: 20.982
|
| 78 |
+
- type: mrr_at_10
|
| 79 |
+
value: 34.094
|
| 80 |
+
- type: mrr_at_100
|
| 81 |
+
value: 35.343
|
| 82 |
+
- type: mrr_at_1000
|
| 83 |
+
value: 35.38
|
| 84 |
+
- type: mrr_at_3
|
| 85 |
+
value: 29.884
|
| 86 |
+
- type: mrr_at_5
|
| 87 |
+
value: 32.141999999999996
|
| 88 |
+
- type: ndcg_at_1
|
| 89 |
+
value: 20.697
|
| 90 |
+
- type: ndcg_at_10
|
| 91 |
+
value: 41.668
|
| 92 |
+
- type: ndcg_at_100
|
| 93 |
+
value: 47.397
|
| 94 |
+
- type: ndcg_at_1000
|
| 95 |
+
value: 48.305
|
| 96 |
+
- type: ndcg_at_3
|
| 97 |
+
value: 32.928000000000004
|
| 98 |
+
- type: ndcg_at_5
|
| 99 |
+
value: 36.998999999999995
|
| 100 |
+
- type: precision_at_1
|
| 101 |
+
value: 20.697
|
| 102 |
+
- type: precision_at_10
|
| 103 |
+
value: 6.636
|
| 104 |
+
- type: precision_at_100
|
| 105 |
+
value: 0.924
|
| 106 |
+
- type: precision_at_1000
|
| 107 |
+
value: 0.099
|
| 108 |
+
- type: precision_at_3
|
| 109 |
+
value: 14.035
|
| 110 |
+
- type: precision_at_5
|
| 111 |
+
value: 10.398
|
| 112 |
+
- type: recall_at_1
|
| 113 |
+
value: 20.697
|
| 114 |
+
- type: recall_at_10
|
| 115 |
+
value: 66.35799999999999
|
| 116 |
+
- type: recall_at_100
|
| 117 |
+
value: 92.39
|
| 118 |
+
- type: recall_at_1000
|
| 119 |
+
value: 99.36
|
| 120 |
+
- type: recall_at_3
|
| 121 |
+
value: 42.105
|
| 122 |
+
- type: recall_at_5
|
| 123 |
+
value: 51.991
|
| 124 |
+
- task:
|
| 125 |
+
type: Clustering
|
| 126 |
+
dataset:
|
| 127 |
+
type: mteb/arxiv-clustering-p2p
|
| 128 |
+
name: MTEB ArxivClusteringP2P
|
| 129 |
+
config: default
|
| 130 |
+
split: test
|
| 131 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
| 132 |
+
metrics:
|
| 133 |
+
- type: v_measure
|
| 134 |
+
value: 42.1169517447068
|
| 135 |
+
- task:
|
| 136 |
+
type: Clustering
|
| 137 |
+
dataset:
|
| 138 |
+
type: mteb/arxiv-clustering-s2s
|
| 139 |
+
name: MTEB ArxivClusteringS2S
|
| 140 |
+
config: default
|
| 141 |
+
split: test
|
| 142 |
+
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
| 143 |
+
metrics:
|
| 144 |
+
- type: v_measure
|
| 145 |
+
value: 34.79553720107097
|
| 146 |
+
- task:
|
| 147 |
+
type: Reranking
|
| 148 |
+
dataset:
|
| 149 |
+
type: mteb/askubuntudupquestions-reranking
|
| 150 |
+
name: MTEB AskUbuntuDupQuestions
|
| 151 |
+
config: default
|
| 152 |
+
split: test
|
| 153 |
+
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
| 154 |
+
metrics:
|
| 155 |
+
- type: map
|
| 156 |
+
value: 58.10811337308168
|
| 157 |
+
- type: mrr
|
| 158 |
+
value: 71.56410763751482
|
| 159 |
+
- task:
|
| 160 |
+
type: STS
|
| 161 |
+
dataset:
|
| 162 |
+
type: mteb/biosses-sts
|
| 163 |
+
name: MTEB BIOSSES
|
| 164 |
+
config: default
|
| 165 |
+
split: test
|
| 166 |
+
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
| 167 |
+
metrics:
|
| 168 |
+
- type: cos_sim_pearson
|
| 169 |
+
value: 78.46834918248696
|
| 170 |
+
- type: cos_sim_spearman
|
| 171 |
+
value: 79.4289182755206
|
| 172 |
+
- type: euclidean_pearson
|
| 173 |
+
value: 76.26662973727008
|
| 174 |
+
- type: euclidean_spearman
|
| 175 |
+
value: 78.11744260952536
|
| 176 |
+
- type: manhattan_pearson
|
| 177 |
+
value: 76.08175262609434
|
| 178 |
+
- type: manhattan_spearman
|
| 179 |
+
value: 78.29395265552289
|
| 180 |
+
- task:
|
| 181 |
+
type: Classification
|
| 182 |
+
dataset:
|
| 183 |
+
type: mteb/banking77
|
| 184 |
+
name: MTEB Banking77Classification
|
| 185 |
+
config: default
|
| 186 |
+
split: test
|
| 187 |
+
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
| 188 |
+
metrics:
|
| 189 |
+
- type: accuracy
|
| 190 |
+
value: 81.63636363636364
|
| 191 |
+
- type: f1
|
| 192 |
+
value: 81.55779952376953
|
| 193 |
+
- task:
|
| 194 |
+
type: Clustering
|
| 195 |
+
dataset:
|
| 196 |
+
type: mteb/biorxiv-clustering-p2p
|
| 197 |
+
name: MTEB BiorxivClusteringP2P
|
| 198 |
+
config: default
|
| 199 |
+
split: test
|
| 200 |
+
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
| 201 |
+
metrics:
|
| 202 |
+
- type: v_measure
|
| 203 |
+
value: 35.88541137137571
|
| 204 |
+
- task:
|
| 205 |
+
type: Clustering
|
| 206 |
+
dataset:
|
| 207 |
+
type: mteb/biorxiv-clustering-s2s
|
| 208 |
+
name: MTEB BiorxivClusteringS2S
|
| 209 |
+
config: default
|
| 210 |
+
split: test
|
| 211 |
+
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
| 212 |
+
metrics:
|
| 213 |
+
- type: v_measure
|
| 214 |
+
value: 30.05205685274407
|
| 215 |
+
- task:
|
| 216 |
+
type: Retrieval
|
| 217 |
+
dataset:
|
| 218 |
+
type: BeIR/cqadupstack
|
| 219 |
+
name: MTEB CQADupstackAndroidRetrieval
|
| 220 |
+
config: default
|
| 221 |
+
split: test
|
| 222 |
+
revision: None
|
| 223 |
+
metrics:
|
| 224 |
+
- type: map_at_1
|
| 225 |
+
value: 30.293999999999997
|
| 226 |
+
- type: map_at_10
|
| 227 |
+
value: 39.876
|
| 228 |
+
- type: map_at_100
|
| 229 |
+
value: 41.315000000000005
|
| 230 |
+
- type: map_at_1000
|
| 231 |
+
value: 41.451
|
| 232 |
+
- type: map_at_3
|
| 233 |
+
value: 37.194
|
| 234 |
+
- type: map_at_5
|
| 235 |
+
value: 38.728
|
| 236 |
+
- type: mrr_at_1
|
| 237 |
+
value: 37.053000000000004
|
| 238 |
+
- type: mrr_at_10
|
| 239 |
+
value: 45.281
|
| 240 |
+
- type: mrr_at_100
|
| 241 |
+
value: 46.188
|
| 242 |
+
- type: mrr_at_1000
|
| 243 |
+
value: 46.245999999999995
|
| 244 |
+
- type: mrr_at_3
|
| 245 |
+
value: 43.228
|
| 246 |
+
- type: mrr_at_5
|
| 247 |
+
value: 44.366
|
| 248 |
+
- type: ndcg_at_1
|
| 249 |
+
value: 37.053000000000004
|
| 250 |
+
- type: ndcg_at_10
|
| 251 |
+
value: 45.086
|
| 252 |
+
- type: ndcg_at_100
|
| 253 |
+
value: 50.756
|
| 254 |
+
- type: ndcg_at_1000
|
| 255 |
+
value: 53.123
|
| 256 |
+
- type: ndcg_at_3
|
| 257 |
+
value: 41.416
|
| 258 |
+
- type: ndcg_at_5
|
| 259 |
+
value: 43.098
|
| 260 |
+
- type: precision_at_1
|
| 261 |
+
value: 37.053000000000004
|
| 262 |
+
- type: precision_at_10
|
| 263 |
+
value: 8.34
|
| 264 |
+
- type: precision_at_100
|
| 265 |
+
value: 1.346
|
| 266 |
+
- type: precision_at_1000
|
| 267 |
+
value: 0.186
|
| 268 |
+
- type: precision_at_3
|
| 269 |
+
value: 19.647000000000002
|
| 270 |
+
- type: precision_at_5
|
| 271 |
+
value: 13.877
|
| 272 |
+
- type: recall_at_1
|
| 273 |
+
value: 30.293999999999997
|
| 274 |
+
- type: recall_at_10
|
| 275 |
+
value: 54.309
|
| 276 |
+
- type: recall_at_100
|
| 277 |
+
value: 78.59
|
| 278 |
+
- type: recall_at_1000
|
| 279 |
+
value: 93.82300000000001
|
| 280 |
+
- type: recall_at_3
|
| 281 |
+
value: 43.168
|
| 282 |
+
- type: recall_at_5
|
| 283 |
+
value: 48.192
|
| 284 |
+
- task:
|
| 285 |
+
type: Retrieval
|
| 286 |
+
dataset:
|
| 287 |
+
type: BeIR/cqadupstack
|
| 288 |
+
name: MTEB CQADupstackEnglishRetrieval
|
| 289 |
+
config: default
|
| 290 |
+
split: test
|
| 291 |
+
revision: None
|
| 292 |
+
metrics:
|
| 293 |
+
- type: map_at_1
|
| 294 |
+
value: 28.738000000000003
|
| 295 |
+
- type: map_at_10
|
| 296 |
+
value: 36.925999999999995
|
| 297 |
+
- type: map_at_100
|
| 298 |
+
value: 38.017
|
| 299 |
+
- type: map_at_1000
|
| 300 |
+
value: 38.144
|
| 301 |
+
- type: map_at_3
|
| 302 |
+
value: 34.446
|
| 303 |
+
- type: map_at_5
|
| 304 |
+
value: 35.704
|
| 305 |
+
- type: mrr_at_1
|
| 306 |
+
value: 35.478
|
| 307 |
+
- type: mrr_at_10
|
| 308 |
+
value: 42.786
|
| 309 |
+
- type: mrr_at_100
|
| 310 |
+
value: 43.458999999999996
|
| 311 |
+
- type: mrr_at_1000
|
| 312 |
+
value: 43.507
|
| 313 |
+
- type: mrr_at_3
|
| 314 |
+
value: 40.648
|
| 315 |
+
- type: mrr_at_5
|
| 316 |
+
value: 41.804
|
| 317 |
+
- type: ndcg_at_1
|
| 318 |
+
value: 35.478
|
| 319 |
+
- type: ndcg_at_10
|
| 320 |
+
value: 42.044
|
| 321 |
+
- type: ndcg_at_100
|
| 322 |
+
value: 46.249
|
| 323 |
+
- type: ndcg_at_1000
|
| 324 |
+
value: 48.44
|
| 325 |
+
- type: ndcg_at_3
|
| 326 |
+
value: 38.314
|
| 327 |
+
- type: ndcg_at_5
|
| 328 |
+
value: 39.798
|
| 329 |
+
- type: precision_at_1
|
| 330 |
+
value: 35.478
|
| 331 |
+
- type: precision_at_10
|
| 332 |
+
value: 7.764
|
| 333 |
+
- type: precision_at_100
|
| 334 |
+
value: 1.253
|
| 335 |
+
- type: precision_at_1000
|
| 336 |
+
value: 0.174
|
| 337 |
+
- type: precision_at_3
|
| 338 |
+
value: 18.047
|
| 339 |
+
- type: precision_at_5
|
| 340 |
+
value: 12.637
|
| 341 |
+
- type: recall_at_1
|
| 342 |
+
value: 28.738000000000003
|
| 343 |
+
- type: recall_at_10
|
| 344 |
+
value: 50.659
|
| 345 |
+
- type: recall_at_100
|
| 346 |
+
value: 68.76299999999999
|
| 347 |
+
- type: recall_at_1000
|
| 348 |
+
value: 82.811
|
| 349 |
+
- type: recall_at_3
|
| 350 |
+
value: 39.536
|
| 351 |
+
- type: recall_at_5
|
| 352 |
+
value: 43.763999999999996
|
| 353 |
+
- task:
|
| 354 |
+
type: Retrieval
|
| 355 |
+
dataset:
|
| 356 |
+
type: BeIR/cqadupstack
|
| 357 |
+
name: MTEB CQADupstackGamingRetrieval
|
| 358 |
+
config: default
|
| 359 |
+
split: test
|
| 360 |
+
revision: None
|
| 361 |
+
metrics:
|
| 362 |
+
- type: map_at_1
|
| 363 |
+
value: 38.565
|
| 364 |
+
- type: map_at_10
|
| 365 |
+
value: 50.168
|
| 366 |
+
- type: map_at_100
|
| 367 |
+
value: 51.11
|
| 368 |
+
- type: map_at_1000
|
| 369 |
+
value: 51.173
|
| 370 |
+
- type: map_at_3
|
| 371 |
+
value: 47.044000000000004
|
| 372 |
+
- type: map_at_5
|
| 373 |
+
value: 48.838
|
| 374 |
+
- type: mrr_at_1
|
| 375 |
+
value: 44.201
|
| 376 |
+
- type: mrr_at_10
|
| 377 |
+
value: 53.596999999999994
|
| 378 |
+
- type: mrr_at_100
|
| 379 |
+
value: 54.211
|
| 380 |
+
- type: mrr_at_1000
|
| 381 |
+
value: 54.247
|
| 382 |
+
- type: mrr_at_3
|
| 383 |
+
value: 51.202000000000005
|
| 384 |
+
- type: mrr_at_5
|
| 385 |
+
value: 52.608999999999995
|
| 386 |
+
- type: ndcg_at_1
|
| 387 |
+
value: 44.201
|
| 388 |
+
- type: ndcg_at_10
|
| 389 |
+
value: 55.694
|
| 390 |
+
- type: ndcg_at_100
|
| 391 |
+
value: 59.518
|
| 392 |
+
- type: ndcg_at_1000
|
| 393 |
+
value: 60.907
|
| 394 |
+
- type: ndcg_at_3
|
| 395 |
+
value: 50.395999999999994
|
| 396 |
+
- type: ndcg_at_5
|
| 397 |
+
value: 53.022999999999996
|
| 398 |
+
- type: precision_at_1
|
| 399 |
+
value: 44.201
|
| 400 |
+
- type: precision_at_10
|
| 401 |
+
value: 8.84
|
| 402 |
+
- type: precision_at_100
|
| 403 |
+
value: 1.162
|
| 404 |
+
- type: precision_at_1000
|
| 405 |
+
value: 0.133
|
| 406 |
+
- type: precision_at_3
|
| 407 |
+
value: 22.153
|
| 408 |
+
- type: precision_at_5
|
| 409 |
+
value: 15.260000000000002
|
| 410 |
+
- type: recall_at_1
|
| 411 |
+
value: 38.565
|
| 412 |
+
- type: recall_at_10
|
| 413 |
+
value: 68.65
|
| 414 |
+
- type: recall_at_100
|
| 415 |
+
value: 85.37400000000001
|
| 416 |
+
- type: recall_at_1000
|
| 417 |
+
value: 95.37400000000001
|
| 418 |
+
- type: recall_at_3
|
| 419 |
+
value: 54.645999999999994
|
| 420 |
+
- type: recall_at_5
|
| 421 |
+
value: 60.958
|
| 422 |
+
- task:
|
| 423 |
+
type: Retrieval
|
| 424 |
+
dataset:
|
| 425 |
+
type: BeIR/cqadupstack
|
| 426 |
+
name: MTEB CQADupstackGisRetrieval
|
| 427 |
+
config: default
|
| 428 |
+
split: test
|
| 429 |
+
revision: None
|
| 430 |
+
metrics:
|
| 431 |
+
- type: map_at_1
|
| 432 |
+
value: 23.945
|
| 433 |
+
- type: map_at_10
|
| 434 |
+
value: 30.641000000000002
|
| 435 |
+
- type: map_at_100
|
| 436 |
+
value: 31.599
|
| 437 |
+
- type: map_at_1000
|
| 438 |
+
value: 31.691000000000003
|
| 439 |
+
- type: map_at_3
|
| 440 |
+
value: 28.405
|
| 441 |
+
- type: map_at_5
|
| 442 |
+
value: 29.704000000000004
|
| 443 |
+
- type: mrr_at_1
|
| 444 |
+
value: 25.537
|
| 445 |
+
- type: mrr_at_10
|
| 446 |
+
value: 32.22
|
| 447 |
+
- type: mrr_at_100
|
| 448 |
+
value: 33.138
|
| 449 |
+
- type: mrr_at_1000
|
| 450 |
+
value: 33.214
|
| 451 |
+
- type: mrr_at_3
|
| 452 |
+
value: 30.151
|
| 453 |
+
- type: mrr_at_5
|
| 454 |
+
value: 31.298
|
| 455 |
+
- type: ndcg_at_1
|
| 456 |
+
value: 25.537
|
| 457 |
+
- type: ndcg_at_10
|
| 458 |
+
value: 34.638000000000005
|
| 459 |
+
- type: ndcg_at_100
|
| 460 |
+
value: 39.486
|
| 461 |
+
- type: ndcg_at_1000
|
| 462 |
+
value: 41.936
|
| 463 |
+
- type: ndcg_at_3
|
| 464 |
+
value: 30.333
|
| 465 |
+
- type: ndcg_at_5
|
| 466 |
+
value: 32.482
|
| 467 |
+
- type: precision_at_1
|
| 468 |
+
value: 25.537
|
| 469 |
+
- type: precision_at_10
|
| 470 |
+
value: 5.153
|
| 471 |
+
- type: precision_at_100
|
| 472 |
+
value: 0.7929999999999999
|
| 473 |
+
- type: precision_at_1000
|
| 474 |
+
value: 0.104
|
| 475 |
+
- type: precision_at_3
|
| 476 |
+
value: 12.429
|
| 477 |
+
- type: precision_at_5
|
| 478 |
+
value: 8.723
|
| 479 |
+
- type: recall_at_1
|
| 480 |
+
value: 23.945
|
| 481 |
+
- type: recall_at_10
|
| 482 |
+
value: 45.412
|
| 483 |
+
- type: recall_at_100
|
| 484 |
+
value: 67.836
|
| 485 |
+
- type: recall_at_1000
|
| 486 |
+
value: 86.467
|
| 487 |
+
- type: recall_at_3
|
| 488 |
+
value: 34.031
|
| 489 |
+
- type: recall_at_5
|
| 490 |
+
value: 39.039
|
| 491 |
+
- task:
|
| 492 |
+
type: Retrieval
|
| 493 |
+
dataset:
|
| 494 |
+
type: BeIR/cqadupstack
|
| 495 |
+
name: MTEB CQADupstackMathematicaRetrieval
|
| 496 |
+
config: default
|
| 497 |
+
split: test
|
| 498 |
+
revision: None
|
| 499 |
+
metrics:
|
| 500 |
+
- type: map_at_1
|
| 501 |
+
value: 14.419
|
| 502 |
+
- type: map_at_10
|
| 503 |
+
value: 20.858999999999998
|
| 504 |
+
- type: map_at_100
|
| 505 |
+
value: 22.067999999999998
|
| 506 |
+
- type: map_at_1000
|
| 507 |
+
value: 22.192
|
| 508 |
+
- type: map_at_3
|
| 509 |
+
value: 18.673000000000002
|
| 510 |
+
- type: map_at_5
|
| 511 |
+
value: 19.968
|
| 512 |
+
- type: mrr_at_1
|
| 513 |
+
value: 17.785999999999998
|
| 514 |
+
- type: mrr_at_10
|
| 515 |
+
value: 24.878
|
| 516 |
+
- type: mrr_at_100
|
| 517 |
+
value: 26.021
|
| 518 |
+
- type: mrr_at_1000
|
| 519 |
+
value: 26.095000000000002
|
| 520 |
+
- type: mrr_at_3
|
| 521 |
+
value: 22.616
|
| 522 |
+
- type: mrr_at_5
|
| 523 |
+
value: 23.785
|
| 524 |
+
- type: ndcg_at_1
|
| 525 |
+
value: 17.785999999999998
|
| 526 |
+
- type: ndcg_at_10
|
| 527 |
+
value: 25.153
|
| 528 |
+
- type: ndcg_at_100
|
| 529 |
+
value: 31.05
|
| 530 |
+
- type: ndcg_at_1000
|
| 531 |
+
value: 34.052
|
| 532 |
+
- type: ndcg_at_3
|
| 533 |
+
value: 21.117
|
| 534 |
+
- type: ndcg_at_5
|
| 535 |
+
value: 23.048
|
| 536 |
+
- type: precision_at_1
|
| 537 |
+
value: 17.785999999999998
|
| 538 |
+
- type: precision_at_10
|
| 539 |
+
value: 4.590000000000001
|
| 540 |
+
- type: precision_at_100
|
| 541 |
+
value: 0.864
|
| 542 |
+
- type: precision_at_1000
|
| 543 |
+
value: 0.125
|
| 544 |
+
- type: precision_at_3
|
| 545 |
+
value: 9.908999999999999
|
| 546 |
+
- type: precision_at_5
|
| 547 |
+
value: 7.313
|
| 548 |
+
- type: recall_at_1
|
| 549 |
+
value: 14.419
|
| 550 |
+
- type: recall_at_10
|
| 551 |
+
value: 34.477999999999994
|
| 552 |
+
- type: recall_at_100
|
| 553 |
+
value: 60.02499999999999
|
| 554 |
+
- type: recall_at_1000
|
| 555 |
+
value: 81.646
|
| 556 |
+
- type: recall_at_3
|
| 557 |
+
value: 23.515
|
| 558 |
+
- type: recall_at_5
|
| 559 |
+
value: 28.266999999999996
|
| 560 |
+
- task:
|
| 561 |
+
type: Retrieval
|
| 562 |
+
dataset:
|
| 563 |
+
type: BeIR/cqadupstack
|
| 564 |
+
name: MTEB CQADupstackPhysicsRetrieval
|
| 565 |
+
config: default
|
| 566 |
+
split: test
|
| 567 |
+
revision: None
|
| 568 |
+
metrics:
|
| 569 |
+
- type: map_at_1
|
| 570 |
+
value: 26.268
|
| 571 |
+
- type: map_at_10
|
| 572 |
+
value: 35.114000000000004
|
| 573 |
+
- type: map_at_100
|
| 574 |
+
value: 36.212
|
| 575 |
+
- type: map_at_1000
|
| 576 |
+
value: 36.333
|
| 577 |
+
- type: map_at_3
|
| 578 |
+
value: 32.436
|
| 579 |
+
- type: map_at_5
|
| 580 |
+
value: 33.992
|
| 581 |
+
- type: mrr_at_1
|
| 582 |
+
value: 31.761
|
| 583 |
+
- type: mrr_at_10
|
| 584 |
+
value: 40.355999999999995
|
| 585 |
+
- type: mrr_at_100
|
| 586 |
+
value: 41.125
|
| 587 |
+
- type: mrr_at_1000
|
| 588 |
+
value: 41.186
|
| 589 |
+
- type: mrr_at_3
|
| 590 |
+
value: 37.937
|
| 591 |
+
- type: mrr_at_5
|
| 592 |
+
value: 39.463
|
| 593 |
+
- type: ndcg_at_1
|
| 594 |
+
value: 31.761
|
| 595 |
+
- type: ndcg_at_10
|
| 596 |
+
value: 40.422000000000004
|
| 597 |
+
- type: ndcg_at_100
|
| 598 |
+
value: 45.458999999999996
|
| 599 |
+
- type: ndcg_at_1000
|
| 600 |
+
value: 47.951
|
| 601 |
+
- type: ndcg_at_3
|
| 602 |
+
value: 35.972
|
| 603 |
+
- type: ndcg_at_5
|
| 604 |
+
value: 38.272
|
| 605 |
+
- type: precision_at_1
|
| 606 |
+
value: 31.761
|
| 607 |
+
- type: precision_at_10
|
| 608 |
+
value: 7.103
|
| 609 |
+
- type: precision_at_100
|
| 610 |
+
value: 1.133
|
| 611 |
+
- type: precision_at_1000
|
| 612 |
+
value: 0.152
|
| 613 |
+
- type: precision_at_3
|
| 614 |
+
value: 16.779
|
| 615 |
+
- type: precision_at_5
|
| 616 |
+
value: 11.877
|
| 617 |
+
- type: recall_at_1
|
| 618 |
+
value: 26.268
|
| 619 |
+
- type: recall_at_10
|
| 620 |
+
value: 51.053000000000004
|
| 621 |
+
- type: recall_at_100
|
| 622 |
+
value: 72.702
|
| 623 |
+
- type: recall_at_1000
|
| 624 |
+
value: 89.521
|
| 625 |
+
- type: recall_at_3
|
| 626 |
+
value: 38.619
|
| 627 |
+
- type: recall_at_5
|
| 628 |
+
value: 44.671
|
| 629 |
+
- task:
|
| 630 |
+
type: Retrieval
|
| 631 |
+
dataset:
|
| 632 |
+
type: BeIR/cqadupstack
|
| 633 |
+
name: MTEB CQADupstackProgrammersRetrieval
|
| 634 |
+
config: default
|
| 635 |
+
split: test
|
| 636 |
+
revision: None
|
| 637 |
+
metrics:
|
| 638 |
+
- type: map_at_1
|
| 639 |
+
value: 25.230999999999998
|
| 640 |
+
- type: map_at_10
|
| 641 |
+
value: 34.227000000000004
|
| 642 |
+
- type: map_at_100
|
| 643 |
+
value: 35.370000000000005
|
| 644 |
+
- type: map_at_1000
|
| 645 |
+
value: 35.488
|
| 646 |
+
- type: map_at_3
|
| 647 |
+
value: 31.496000000000002
|
| 648 |
+
- type: map_at_5
|
| 649 |
+
value: 33.034
|
| 650 |
+
- type: mrr_at_1
|
| 651 |
+
value: 30.822
|
| 652 |
+
- type: mrr_at_10
|
| 653 |
+
value: 39.045
|
| 654 |
+
- type: mrr_at_100
|
| 655 |
+
value: 39.809
|
| 656 |
+
- type: mrr_at_1000
|
| 657 |
+
value: 39.873
|
| 658 |
+
- type: mrr_at_3
|
| 659 |
+
value: 36.663000000000004
|
| 660 |
+
- type: mrr_at_5
|
| 661 |
+
value: 37.964
|
| 662 |
+
- type: ndcg_at_1
|
| 663 |
+
value: 30.822
|
| 664 |
+
- type: ndcg_at_10
|
| 665 |
+
value: 39.472
|
| 666 |
+
- type: ndcg_at_100
|
| 667 |
+
value: 44.574999999999996
|
| 668 |
+
- type: ndcg_at_1000
|
| 669 |
+
value: 47.162
|
| 670 |
+
- type: ndcg_at_3
|
| 671 |
+
value: 34.929
|
| 672 |
+
- type: ndcg_at_5
|
| 673 |
+
value: 37.002
|
| 674 |
+
- type: precision_at_1
|
| 675 |
+
value: 30.822
|
| 676 |
+
- type: precision_at_10
|
| 677 |
+
value: 7.055
|
| 678 |
+
- type: precision_at_100
|
| 679 |
+
value: 1.124
|
| 680 |
+
- type: precision_at_1000
|
| 681 |
+
value: 0.152
|
| 682 |
+
- type: precision_at_3
|
| 683 |
+
value: 16.591
|
| 684 |
+
- type: precision_at_5
|
| 685 |
+
value: 11.667
|
| 686 |
+
- type: recall_at_1
|
| 687 |
+
value: 25.230999999999998
|
| 688 |
+
- type: recall_at_10
|
| 689 |
+
value: 50.42100000000001
|
| 690 |
+
- type: recall_at_100
|
| 691 |
+
value: 72.685
|
| 692 |
+
- type: recall_at_1000
|
| 693 |
+
value: 90.469
|
| 694 |
+
- type: recall_at_3
|
| 695 |
+
value: 37.503
|
| 696 |
+
- type: recall_at_5
|
| 697 |
+
value: 43.123
|
| 698 |
+
- task:
|
| 699 |
+
type: Retrieval
|
| 700 |
+
dataset:
|
| 701 |
+
type: BeIR/cqadupstack
|
| 702 |
+
name: MTEB CQADupstackRetrieval
|
| 703 |
+
config: default
|
| 704 |
+
split: test
|
| 705 |
+
revision: None
|
| 706 |
+
metrics:
|
| 707 |
+
- type: map_at_1
|
| 708 |
+
value: 24.604166666666664
|
| 709 |
+
- type: map_at_10
|
| 710 |
+
value: 32.427166666666665
|
| 711 |
+
- type: map_at_100
|
| 712 |
+
value: 33.51474999999999
|
| 713 |
+
- type: map_at_1000
|
| 714 |
+
value: 33.6345
|
| 715 |
+
- type: map_at_3
|
| 716 |
+
value: 30.02366666666667
|
| 717 |
+
- type: map_at_5
|
| 718 |
+
value: 31.382333333333328
|
| 719 |
+
- type: mrr_at_1
|
| 720 |
+
value: 29.001166666666666
|
| 721 |
+
- type: mrr_at_10
|
| 722 |
+
value: 36.3315
|
| 723 |
+
- type: mrr_at_100
|
| 724 |
+
value: 37.16683333333333
|
| 725 |
+
- type: mrr_at_1000
|
| 726 |
+
value: 37.23341666666668
|
| 727 |
+
- type: mrr_at_3
|
| 728 |
+
value: 34.19916666666667
|
| 729 |
+
- type: mrr_at_5
|
| 730 |
+
value: 35.40458333333334
|
| 731 |
+
- type: ndcg_at_1
|
| 732 |
+
value: 29.001166666666666
|
| 733 |
+
- type: ndcg_at_10
|
| 734 |
+
value: 37.06883333333334
|
| 735 |
+
- type: ndcg_at_100
|
| 736 |
+
value: 41.95816666666666
|
| 737 |
+
- type: ndcg_at_1000
|
| 738 |
+
value: 44.501583333333336
|
| 739 |
+
- type: ndcg_at_3
|
| 740 |
+
value: 32.973499999999994
|
| 741 |
+
- type: ndcg_at_5
|
| 742 |
+
value: 34.90833333333334
|
| 743 |
+
- type: precision_at_1
|
| 744 |
+
value: 29.001166666666666
|
| 745 |
+
- type: precision_at_10
|
| 746 |
+
value: 6.336
|
| 747 |
+
- type: precision_at_100
|
| 748 |
+
value: 1.0282499999999999
|
| 749 |
+
- type: precision_at_1000
|
| 750 |
+
value: 0.14391666666666664
|
| 751 |
+
- type: precision_at_3
|
| 752 |
+
value: 14.932499999999996
|
| 753 |
+
- type: precision_at_5
|
| 754 |
+
value: 10.50825
|
| 755 |
+
- type: recall_at_1
|
| 756 |
+
value: 24.604166666666664
|
| 757 |
+
- type: recall_at_10
|
| 758 |
+
value: 46.9525
|
| 759 |
+
- type: recall_at_100
|
| 760 |
+
value: 68.67816666666667
|
| 761 |
+
- type: recall_at_1000
|
| 762 |
+
value: 86.59783333333334
|
| 763 |
+
- type: recall_at_3
|
| 764 |
+
value: 35.49783333333333
|
| 765 |
+
- type: recall_at_5
|
| 766 |
+
value: 40.52525000000001
|
| 767 |
+
- task:
|
| 768 |
+
type: Retrieval
|
| 769 |
+
dataset:
|
| 770 |
+
type: BeIR/cqadupstack
|
| 771 |
+
name: MTEB CQADupstackStatsRetrieval
|
| 772 |
+
config: default
|
| 773 |
+
split: test
|
| 774 |
+
revision: None
|
| 775 |
+
metrics:
|
| 776 |
+
- type: map_at_1
|
| 777 |
+
value: 23.559
|
| 778 |
+
- type: map_at_10
|
| 779 |
+
value: 29.023
|
| 780 |
+
- type: map_at_100
|
| 781 |
+
value: 29.818
|
| 782 |
+
- type: map_at_1000
|
| 783 |
+
value: 29.909000000000002
|
| 784 |
+
- type: map_at_3
|
| 785 |
+
value: 27.037
|
| 786 |
+
- type: map_at_5
|
| 787 |
+
value: 28.225
|
| 788 |
+
- type: mrr_at_1
|
| 789 |
+
value: 26.994
|
| 790 |
+
- type: mrr_at_10
|
| 791 |
+
value: 31.962000000000003
|
| 792 |
+
- type: mrr_at_100
|
| 793 |
+
value: 32.726
|
| 794 |
+
- type: mrr_at_1000
|
| 795 |
+
value: 32.800000000000004
|
| 796 |
+
- type: mrr_at_3
|
| 797 |
+
value: 30.266
|
| 798 |
+
- type: mrr_at_5
|
| 799 |
+
value: 31.208999999999996
|
| 800 |
+
- type: ndcg_at_1
|
| 801 |
+
value: 26.994
|
| 802 |
+
- type: ndcg_at_10
|
| 803 |
+
value: 32.53
|
| 804 |
+
- type: ndcg_at_100
|
| 805 |
+
value: 36.758
|
| 806 |
+
- type: ndcg_at_1000
|
| 807 |
+
value: 39.362
|
| 808 |
+
- type: ndcg_at_3
|
| 809 |
+
value: 28.985
|
| 810 |
+
- type: ndcg_at_5
|
| 811 |
+
value: 30.757
|
| 812 |
+
- type: precision_at_1
|
| 813 |
+
value: 26.994
|
| 814 |
+
- type: precision_at_10
|
| 815 |
+
value: 4.968999999999999
|
| 816 |
+
- type: precision_at_100
|
| 817 |
+
value: 0.759
|
| 818 |
+
- type: precision_at_1000
|
| 819 |
+
value: 0.106
|
| 820 |
+
- type: precision_at_3
|
| 821 |
+
value: 12.219
|
| 822 |
+
- type: precision_at_5
|
| 823 |
+
value: 8.527999999999999
|
| 824 |
+
- type: recall_at_1
|
| 825 |
+
value: 23.559
|
| 826 |
+
- type: recall_at_10
|
| 827 |
+
value: 40.585
|
| 828 |
+
- type: recall_at_100
|
| 829 |
+
value: 60.306000000000004
|
| 830 |
+
- type: recall_at_1000
|
| 831 |
+
value: 80.11
|
| 832 |
+
- type: recall_at_3
|
| 833 |
+
value: 30.794
|
| 834 |
+
- type: recall_at_5
|
| 835 |
+
value: 35.186
|
| 836 |
+
- task:
|
| 837 |
+
type: Retrieval
|
| 838 |
+
dataset:
|
| 839 |
+
type: BeIR/cqadupstack
|
| 840 |
+
name: MTEB CQADupstackTexRetrieval
|
| 841 |
+
config: default
|
| 842 |
+
split: test
|
| 843 |
+
revision: None
|
| 844 |
+
metrics:
|
| 845 |
+
- type: map_at_1
|
| 846 |
+
value: 16.384999999999998
|
| 847 |
+
- type: map_at_10
|
| 848 |
+
value: 22.142
|
| 849 |
+
- type: map_at_100
|
| 850 |
+
value: 23.057
|
| 851 |
+
- type: map_at_1000
|
| 852 |
+
value: 23.177
|
| 853 |
+
- type: map_at_3
|
| 854 |
+
value: 20.29
|
| 855 |
+
- type: map_at_5
|
| 856 |
+
value: 21.332
|
| 857 |
+
- type: mrr_at_1
|
| 858 |
+
value: 19.89
|
| 859 |
+
- type: mrr_at_10
|
| 860 |
+
value: 25.771
|
| 861 |
+
- type: mrr_at_100
|
| 862 |
+
value: 26.599
|
| 863 |
+
- type: mrr_at_1000
|
| 864 |
+
value: 26.680999999999997
|
| 865 |
+
- type: mrr_at_3
|
| 866 |
+
value: 23.962
|
| 867 |
+
- type: mrr_at_5
|
| 868 |
+
value: 24.934
|
| 869 |
+
- type: ndcg_at_1
|
| 870 |
+
value: 19.89
|
| 871 |
+
- type: ndcg_at_10
|
| 872 |
+
value: 25.97
|
| 873 |
+
- type: ndcg_at_100
|
| 874 |
+
value: 30.605
|
| 875 |
+
- type: ndcg_at_1000
|
| 876 |
+
value: 33.619
|
| 877 |
+
- type: ndcg_at_3
|
| 878 |
+
value: 22.704
|
| 879 |
+
- type: ndcg_at_5
|
| 880 |
+
value: 24.199
|
| 881 |
+
- type: precision_at_1
|
| 882 |
+
value: 19.89
|
| 883 |
+
- type: precision_at_10
|
| 884 |
+
value: 4.553
|
| 885 |
+
- type: precision_at_100
|
| 886 |
+
value: 0.8049999999999999
|
| 887 |
+
- type: precision_at_1000
|
| 888 |
+
value: 0.122
|
| 889 |
+
- type: precision_at_3
|
| 890 |
+
value: 10.541
|
| 891 |
+
- type: precision_at_5
|
| 892 |
+
value: 7.46
|
| 893 |
+
- type: recall_at_1
|
| 894 |
+
value: 16.384999999999998
|
| 895 |
+
- type: recall_at_10
|
| 896 |
+
value: 34.001
|
| 897 |
+
- type: recall_at_100
|
| 898 |
+
value: 55.17100000000001
|
| 899 |
+
- type: recall_at_1000
|
| 900 |
+
value: 77.125
|
| 901 |
+
- type: recall_at_3
|
| 902 |
+
value: 24.618000000000002
|
| 903 |
+
- type: recall_at_5
|
| 904 |
+
value: 28.695999999999998
|
| 905 |
+
- task:
|
| 906 |
+
type: Retrieval
|
| 907 |
+
dataset:
|
| 908 |
+
type: BeIR/cqadupstack
|
| 909 |
+
name: MTEB CQADupstackUnixRetrieval
|
| 910 |
+
config: default
|
| 911 |
+
split: test
|
| 912 |
+
revision: None
|
| 913 |
+
metrics:
|
| 914 |
+
- type: map_at_1
|
| 915 |
+
value: 23.726
|
| 916 |
+
- type: map_at_10
|
| 917 |
+
value: 31.227
|
| 918 |
+
- type: map_at_100
|
| 919 |
+
value: 32.311
|
| 920 |
+
- type: map_at_1000
|
| 921 |
+
value: 32.419
|
| 922 |
+
- type: map_at_3
|
| 923 |
+
value: 28.765
|
| 924 |
+
- type: map_at_5
|
| 925 |
+
value: 30.229
|
| 926 |
+
- type: mrr_at_1
|
| 927 |
+
value: 27.705000000000002
|
| 928 |
+
- type: mrr_at_10
|
| 929 |
+
value: 35.085
|
| 930 |
+
- type: mrr_at_100
|
| 931 |
+
value: 35.931000000000004
|
| 932 |
+
- type: mrr_at_1000
|
| 933 |
+
value: 36
|
| 934 |
+
- type: mrr_at_3
|
| 935 |
+
value: 32.603
|
| 936 |
+
- type: mrr_at_5
|
| 937 |
+
value: 34.117999999999995
|
| 938 |
+
- type: ndcg_at_1
|
| 939 |
+
value: 27.705000000000002
|
| 940 |
+
- type: ndcg_at_10
|
| 941 |
+
value: 35.968
|
| 942 |
+
- type: ndcg_at_100
|
| 943 |
+
value: 41.197
|
| 944 |
+
- type: ndcg_at_1000
|
| 945 |
+
value: 43.76
|
| 946 |
+
- type: ndcg_at_3
|
| 947 |
+
value: 31.304
|
| 948 |
+
- type: ndcg_at_5
|
| 949 |
+
value: 33.661
|
| 950 |
+
- type: precision_at_1
|
| 951 |
+
value: 27.705000000000002
|
| 952 |
+
- type: precision_at_10
|
| 953 |
+
value: 5.942
|
| 954 |
+
- type: precision_at_100
|
| 955 |
+
value: 0.964
|
| 956 |
+
- type: precision_at_1000
|
| 957 |
+
value: 0.13
|
| 958 |
+
- type: precision_at_3
|
| 959 |
+
value: 13.868
|
| 960 |
+
- type: precision_at_5
|
| 961 |
+
value: 9.944
|
| 962 |
+
- type: recall_at_1
|
| 963 |
+
value: 23.726
|
| 964 |
+
- type: recall_at_10
|
| 965 |
+
value: 46.786
|
| 966 |
+
- type: recall_at_100
|
| 967 |
+
value: 70.072
|
| 968 |
+
- type: recall_at_1000
|
| 969 |
+
value: 88.2
|
| 970 |
+
- type: recall_at_3
|
| 971 |
+
value: 33.981
|
| 972 |
+
- type: recall_at_5
|
| 973 |
+
value: 39.893
|
| 974 |
+
- task:
|
| 975 |
+
type: Retrieval
|
| 976 |
+
dataset:
|
| 977 |
+
type: BeIR/cqadupstack
|
| 978 |
+
name: MTEB CQADupstackWebmastersRetrieval
|
| 979 |
+
config: default
|
| 980 |
+
split: test
|
| 981 |
+
revision: None
|
| 982 |
+
metrics:
|
| 983 |
+
- type: map_at_1
|
| 984 |
+
value: 23.344
|
| 985 |
+
- type: map_at_10
|
| 986 |
+
value: 31.636999999999997
|
| 987 |
+
- type: map_at_100
|
| 988 |
+
value: 33.065
|
| 989 |
+
- type: map_at_1000
|
| 990 |
+
value: 33.300000000000004
|
| 991 |
+
- type: map_at_3
|
| 992 |
+
value: 29.351
|
| 993 |
+
- type: map_at_5
|
| 994 |
+
value: 30.432
|
| 995 |
+
- type: mrr_at_1
|
| 996 |
+
value: 27.866000000000003
|
| 997 |
+
- type: mrr_at_10
|
| 998 |
+
value: 35.587
|
| 999 |
+
- type: mrr_at_100
|
| 1000 |
+
value: 36.52
|
| 1001 |
+
- type: mrr_at_1000
|
| 1002 |
+
value: 36.597
|
| 1003 |
+
- type: mrr_at_3
|
| 1004 |
+
value: 33.696
|
| 1005 |
+
- type: mrr_at_5
|
| 1006 |
+
value: 34.713
|
| 1007 |
+
- type: ndcg_at_1
|
| 1008 |
+
value: 27.866000000000003
|
| 1009 |
+
- type: ndcg_at_10
|
| 1010 |
+
value: 36.61
|
| 1011 |
+
- type: ndcg_at_100
|
| 1012 |
+
value: 41.88
|
| 1013 |
+
- type: ndcg_at_1000
|
| 1014 |
+
value: 45.105000000000004
|
| 1015 |
+
- type: ndcg_at_3
|
| 1016 |
+
value: 33.038000000000004
|
| 1017 |
+
- type: ndcg_at_5
|
| 1018 |
+
value: 34.331
|
| 1019 |
+
- type: precision_at_1
|
| 1020 |
+
value: 27.866000000000003
|
| 1021 |
+
- type: precision_at_10
|
| 1022 |
+
value: 6.917
|
| 1023 |
+
- type: precision_at_100
|
| 1024 |
+
value: 1.3599999999999999
|
| 1025 |
+
- type: precision_at_1000
|
| 1026 |
+
value: 0.233
|
| 1027 |
+
- type: precision_at_3
|
| 1028 |
+
value: 15.547
|
| 1029 |
+
- type: precision_at_5
|
| 1030 |
+
value: 10.791
|
| 1031 |
+
- type: recall_at_1
|
| 1032 |
+
value: 23.344
|
| 1033 |
+
- type: recall_at_10
|
| 1034 |
+
value: 45.782000000000004
|
| 1035 |
+
- type: recall_at_100
|
| 1036 |
+
value: 69.503
|
| 1037 |
+
- type: recall_at_1000
|
| 1038 |
+
value: 90.742
|
| 1039 |
+
- type: recall_at_3
|
| 1040 |
+
value: 35.160000000000004
|
| 1041 |
+
- type: recall_at_5
|
| 1042 |
+
value: 39.058
|
| 1043 |
+
- task:
|
| 1044 |
+
type: Retrieval
|
| 1045 |
+
dataset:
|
| 1046 |
+
type: BeIR/cqadupstack
|
| 1047 |
+
name: MTEB CQADupstackWordpressRetrieval
|
| 1048 |
+
config: default
|
| 1049 |
+
split: test
|
| 1050 |
+
revision: None
|
| 1051 |
+
metrics:
|
| 1052 |
+
- type: map_at_1
|
| 1053 |
+
value: 20.776
|
| 1054 |
+
- type: map_at_10
|
| 1055 |
+
value: 27.285999999999998
|
| 1056 |
+
- type: map_at_100
|
| 1057 |
+
value: 28.235
|
| 1058 |
+
- type: map_at_1000
|
| 1059 |
+
value: 28.337
|
| 1060 |
+
- type: map_at_3
|
| 1061 |
+
value: 25.147000000000002
|
| 1062 |
+
- type: map_at_5
|
| 1063 |
+
value: 26.401999999999997
|
| 1064 |
+
- type: mrr_at_1
|
| 1065 |
+
value: 22.921
|
| 1066 |
+
- type: mrr_at_10
|
| 1067 |
+
value: 29.409999999999997
|
| 1068 |
+
- type: mrr_at_100
|
| 1069 |
+
value: 30.275000000000002
|
| 1070 |
+
- type: mrr_at_1000
|
| 1071 |
+
value: 30.354999999999997
|
| 1072 |
+
- type: mrr_at_3
|
| 1073 |
+
value: 27.418
|
| 1074 |
+
- type: mrr_at_5
|
| 1075 |
+
value: 28.592000000000002
|
| 1076 |
+
- type: ndcg_at_1
|
| 1077 |
+
value: 22.921
|
| 1078 |
+
- type: ndcg_at_10
|
| 1079 |
+
value: 31.239
|
| 1080 |
+
- type: ndcg_at_100
|
| 1081 |
+
value: 35.965
|
| 1082 |
+
- type: ndcg_at_1000
|
| 1083 |
+
value: 38.602
|
| 1084 |
+
- type: ndcg_at_3
|
| 1085 |
+
value: 27.174
|
| 1086 |
+
- type: ndcg_at_5
|
| 1087 |
+
value: 29.229
|
| 1088 |
+
- type: precision_at_1
|
| 1089 |
+
value: 22.921
|
| 1090 |
+
- type: precision_at_10
|
| 1091 |
+
value: 4.806
|
| 1092 |
+
- type: precision_at_100
|
| 1093 |
+
value: 0.776
|
| 1094 |
+
- type: precision_at_1000
|
| 1095 |
+
value: 0.11
|
| 1096 |
+
- type: precision_at_3
|
| 1097 |
+
value: 11.459999999999999
|
| 1098 |
+
- type: precision_at_5
|
| 1099 |
+
value: 8.022
|
| 1100 |
+
- type: recall_at_1
|
| 1101 |
+
value: 20.776
|
| 1102 |
+
- type: recall_at_10
|
| 1103 |
+
value: 41.294
|
| 1104 |
+
- type: recall_at_100
|
| 1105 |
+
value: 63.111
|
| 1106 |
+
- type: recall_at_1000
|
| 1107 |
+
value: 82.88600000000001
|
| 1108 |
+
- type: recall_at_3
|
| 1109 |
+
value: 30.403000000000002
|
| 1110 |
+
- type: recall_at_5
|
| 1111 |
+
value: 35.455999999999996
|
| 1112 |
+
- task:
|
| 1113 |
+
type: Retrieval
|
| 1114 |
+
dataset:
|
| 1115 |
+
type: climate-fever
|
| 1116 |
+
name: MTEB ClimateFEVER
|
| 1117 |
+
config: default
|
| 1118 |
+
split: test
|
| 1119 |
+
revision: None
|
| 1120 |
+
metrics:
|
| 1121 |
+
- type: map_at_1
|
| 1122 |
+
value: 9.376
|
| 1123 |
+
- type: map_at_10
|
| 1124 |
+
value: 15.926000000000002
|
| 1125 |
+
- type: map_at_100
|
| 1126 |
+
value: 17.585
|
| 1127 |
+
- type: map_at_1000
|
| 1128 |
+
value: 17.776
|
| 1129 |
+
- type: map_at_3
|
| 1130 |
+
value: 13.014000000000001
|
| 1131 |
+
- type: map_at_5
|
| 1132 |
+
value: 14.417
|
| 1133 |
+
- type: mrr_at_1
|
| 1134 |
+
value: 20.195
|
| 1135 |
+
- type: mrr_at_10
|
| 1136 |
+
value: 29.95
|
| 1137 |
+
- type: mrr_at_100
|
| 1138 |
+
value: 31.052000000000003
|
| 1139 |
+
- type: mrr_at_1000
|
| 1140 |
+
value: 31.108000000000004
|
| 1141 |
+
- type: mrr_at_3
|
| 1142 |
+
value: 26.667
|
| 1143 |
+
- type: mrr_at_5
|
| 1144 |
+
value: 28.458
|
| 1145 |
+
- type: ndcg_at_1
|
| 1146 |
+
value: 20.195
|
| 1147 |
+
- type: ndcg_at_10
|
| 1148 |
+
value: 22.871
|
| 1149 |
+
- type: ndcg_at_100
|
| 1150 |
+
value: 29.921999999999997
|
| 1151 |
+
- type: ndcg_at_1000
|
| 1152 |
+
value: 33.672999999999995
|
| 1153 |
+
- type: ndcg_at_3
|
| 1154 |
+
value: 17.782999999999998
|
| 1155 |
+
- type: ndcg_at_5
|
| 1156 |
+
value: 19.544
|
| 1157 |
+
- type: precision_at_1
|
| 1158 |
+
value: 20.195
|
| 1159 |
+
- type: precision_at_10
|
| 1160 |
+
value: 7.394
|
| 1161 |
+
- type: precision_at_100
|
| 1162 |
+
value: 1.493
|
| 1163 |
+
- type: precision_at_1000
|
| 1164 |
+
value: 0.218
|
| 1165 |
+
- type: precision_at_3
|
| 1166 |
+
value: 13.073
|
| 1167 |
+
- type: precision_at_5
|
| 1168 |
+
value: 10.436
|
| 1169 |
+
- type: recall_at_1
|
| 1170 |
+
value: 9.376
|
| 1171 |
+
- type: recall_at_10
|
| 1172 |
+
value: 28.544999999999998
|
| 1173 |
+
- type: recall_at_100
|
| 1174 |
+
value: 53.147999999999996
|
| 1175 |
+
- type: recall_at_1000
|
| 1176 |
+
value: 74.62
|
| 1177 |
+
- type: recall_at_3
|
| 1178 |
+
value: 16.464000000000002
|
| 1179 |
+
- type: recall_at_5
|
| 1180 |
+
value: 21.004
|
| 1181 |
+
- task:
|
| 1182 |
+
type: Retrieval
|
| 1183 |
+
dataset:
|
| 1184 |
+
type: dbpedia-entity
|
| 1185 |
+
name: MTEB DBPedia
|
| 1186 |
+
config: default
|
| 1187 |
+
split: test
|
| 1188 |
+
revision: None
|
| 1189 |
+
metrics:
|
| 1190 |
+
- type: map_at_1
|
| 1191 |
+
value: 8.415000000000001
|
| 1192 |
+
- type: map_at_10
|
| 1193 |
+
value: 18.738
|
| 1194 |
+
- type: map_at_100
|
| 1195 |
+
value: 27.291999999999998
|
| 1196 |
+
- type: map_at_1000
|
| 1197 |
+
value: 28.992
|
| 1198 |
+
- type: map_at_3
|
| 1199 |
+
value: 13.196
|
| 1200 |
+
- type: map_at_5
|
| 1201 |
+
value: 15.539
|
| 1202 |
+
- type: mrr_at_1
|
| 1203 |
+
value: 66.5
|
| 1204 |
+
- type: mrr_at_10
|
| 1205 |
+
value: 74.518
|
| 1206 |
+
- type: mrr_at_100
|
| 1207 |
+
value: 74.86
|
| 1208 |
+
- type: mrr_at_1000
|
| 1209 |
+
value: 74.87
|
| 1210 |
+
- type: mrr_at_3
|
| 1211 |
+
value: 72.375
|
| 1212 |
+
- type: mrr_at_5
|
| 1213 |
+
value: 73.86200000000001
|
| 1214 |
+
- type: ndcg_at_1
|
| 1215 |
+
value: 54.37499999999999
|
| 1216 |
+
- type: ndcg_at_10
|
| 1217 |
+
value: 41.317
|
| 1218 |
+
- type: ndcg_at_100
|
| 1219 |
+
value: 45.845
|
| 1220 |
+
- type: ndcg_at_1000
|
| 1221 |
+
value: 52.92
|
| 1222 |
+
- type: ndcg_at_3
|
| 1223 |
+
value: 44.983000000000004
|
| 1224 |
+
- type: ndcg_at_5
|
| 1225 |
+
value: 42.989
|
| 1226 |
+
- type: precision_at_1
|
| 1227 |
+
value: 66.5
|
| 1228 |
+
- type: precision_at_10
|
| 1229 |
+
value: 33.6
|
| 1230 |
+
- type: precision_at_100
|
| 1231 |
+
value: 10.972999999999999
|
| 1232 |
+
- type: precision_at_1000
|
| 1233 |
+
value: 2.214
|
| 1234 |
+
- type: precision_at_3
|
| 1235 |
+
value: 48.583
|
| 1236 |
+
- type: precision_at_5
|
| 1237 |
+
value: 42.15
|
| 1238 |
+
- type: recall_at_1
|
| 1239 |
+
value: 8.415000000000001
|
| 1240 |
+
- type: recall_at_10
|
| 1241 |
+
value: 24.953
|
| 1242 |
+
- type: recall_at_100
|
| 1243 |
+
value: 52.48199999999999
|
| 1244 |
+
- type: recall_at_1000
|
| 1245 |
+
value: 75.093
|
| 1246 |
+
- type: recall_at_3
|
| 1247 |
+
value: 14.341000000000001
|
| 1248 |
+
- type: recall_at_5
|
| 1249 |
+
value: 18.468
|
| 1250 |
+
- task:
|
| 1251 |
+
type: Classification
|
| 1252 |
+
dataset:
|
| 1253 |
+
type: mteb/emotion
|
| 1254 |
+
name: MTEB EmotionClassification
|
| 1255 |
+
config: default
|
| 1256 |
+
split: test
|
| 1257 |
+
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
| 1258 |
+
metrics:
|
| 1259 |
+
- type: accuracy
|
| 1260 |
+
value: 47.06499999999999
|
| 1261 |
+
- type: f1
|
| 1262 |
+
value: 41.439327599975385
|
| 1263 |
+
- task:
|
| 1264 |
+
type: Retrieval
|
| 1265 |
+
dataset:
|
| 1266 |
+
type: fever
|
| 1267 |
+
name: MTEB FEVER
|
| 1268 |
+
config: default
|
| 1269 |
+
split: test
|
| 1270 |
+
revision: None
|
| 1271 |
+
metrics:
|
| 1272 |
+
- type: map_at_1
|
| 1273 |
+
value: 66.02
|
| 1274 |
+
- type: map_at_10
|
| 1275 |
+
value: 76.68599999999999
|
| 1276 |
+
- type: map_at_100
|
| 1277 |
+
value: 76.959
|
| 1278 |
+
- type: map_at_1000
|
| 1279 |
+
value: 76.972
|
| 1280 |
+
- type: map_at_3
|
| 1281 |
+
value: 75.024
|
| 1282 |
+
- type: map_at_5
|
| 1283 |
+
value: 76.153
|
| 1284 |
+
- type: mrr_at_1
|
| 1285 |
+
value: 71.197
|
| 1286 |
+
- type: mrr_at_10
|
| 1287 |
+
value: 81.105
|
| 1288 |
+
- type: mrr_at_100
|
| 1289 |
+
value: 81.232
|
| 1290 |
+
- type: mrr_at_1000
|
| 1291 |
+
value: 81.233
|
| 1292 |
+
- type: mrr_at_3
|
| 1293 |
+
value: 79.758
|
| 1294 |
+
- type: mrr_at_5
|
| 1295 |
+
value: 80.69
|
| 1296 |
+
- type: ndcg_at_1
|
| 1297 |
+
value: 71.197
|
| 1298 |
+
- type: ndcg_at_10
|
| 1299 |
+
value: 81.644
|
| 1300 |
+
- type: ndcg_at_100
|
| 1301 |
+
value: 82.645
|
| 1302 |
+
- type: ndcg_at_1000
|
| 1303 |
+
value: 82.879
|
| 1304 |
+
- type: ndcg_at_3
|
| 1305 |
+
value: 78.792
|
| 1306 |
+
- type: ndcg_at_5
|
| 1307 |
+
value: 80.528
|
| 1308 |
+
- type: precision_at_1
|
| 1309 |
+
value: 71.197
|
| 1310 |
+
- type: precision_at_10
|
| 1311 |
+
value: 10.206999999999999
|
| 1312 |
+
- type: precision_at_100
|
| 1313 |
+
value: 1.093
|
| 1314 |
+
- type: precision_at_1000
|
| 1315 |
+
value: 0.11299999999999999
|
| 1316 |
+
- type: precision_at_3
|
| 1317 |
+
value: 30.868000000000002
|
| 1318 |
+
- type: precision_at_5
|
| 1319 |
+
value: 19.559
|
| 1320 |
+
- type: recall_at_1
|
| 1321 |
+
value: 66.02
|
| 1322 |
+
- type: recall_at_10
|
| 1323 |
+
value: 92.50699999999999
|
| 1324 |
+
- type: recall_at_100
|
| 1325 |
+
value: 96.497
|
| 1326 |
+
- type: recall_at_1000
|
| 1327 |
+
value: 97.956
|
| 1328 |
+
- type: recall_at_3
|
| 1329 |
+
value: 84.866
|
| 1330 |
+
- type: recall_at_5
|
| 1331 |
+
value: 89.16199999999999
|
| 1332 |
+
- task:
|
| 1333 |
+
type: Retrieval
|
| 1334 |
+
dataset:
|
| 1335 |
+
type: fiqa
|
| 1336 |
+
name: MTEB FiQA2018
|
| 1337 |
+
config: default
|
| 1338 |
+
split: test
|
| 1339 |
+
revision: None
|
| 1340 |
+
metrics:
|
| 1341 |
+
- type: map_at_1
|
| 1342 |
+
value: 17.948
|
| 1343 |
+
- type: map_at_10
|
| 1344 |
+
value: 29.833
|
| 1345 |
+
- type: map_at_100
|
| 1346 |
+
value: 31.487
|
| 1347 |
+
- type: map_at_1000
|
| 1348 |
+
value: 31.674000000000003
|
| 1349 |
+
- type: map_at_3
|
| 1350 |
+
value: 26.029999999999998
|
| 1351 |
+
- type: map_at_5
|
| 1352 |
+
value: 28.038999999999998
|
| 1353 |
+
- type: mrr_at_1
|
| 1354 |
+
value: 34.721999999999994
|
| 1355 |
+
- type: mrr_at_10
|
| 1356 |
+
value: 44.214999999999996
|
| 1357 |
+
- type: mrr_at_100
|
| 1358 |
+
value: 44.994
|
| 1359 |
+
- type: mrr_at_1000
|
| 1360 |
+
value: 45.051
|
| 1361 |
+
- type: mrr_at_3
|
| 1362 |
+
value: 41.667
|
| 1363 |
+
- type: mrr_at_5
|
| 1364 |
+
value: 43.032
|
| 1365 |
+
- type: ndcg_at_1
|
| 1366 |
+
value: 34.721999999999994
|
| 1367 |
+
- type: ndcg_at_10
|
| 1368 |
+
value: 37.434
|
| 1369 |
+
- type: ndcg_at_100
|
| 1370 |
+
value: 43.702000000000005
|
| 1371 |
+
- type: ndcg_at_1000
|
| 1372 |
+
value: 46.993
|
| 1373 |
+
- type: ndcg_at_3
|
| 1374 |
+
value: 33.56
|
| 1375 |
+
- type: ndcg_at_5
|
| 1376 |
+
value: 34.687
|
| 1377 |
+
- type: precision_at_1
|
| 1378 |
+
value: 34.721999999999994
|
| 1379 |
+
- type: precision_at_10
|
| 1380 |
+
value: 10.401
|
| 1381 |
+
- type: precision_at_100
|
| 1382 |
+
value: 1.7049999999999998
|
| 1383 |
+
- type: precision_at_1000
|
| 1384 |
+
value: 0.22799999999999998
|
| 1385 |
+
- type: precision_at_3
|
| 1386 |
+
value: 22.531000000000002
|
| 1387 |
+
- type: precision_at_5
|
| 1388 |
+
value: 16.42
|
| 1389 |
+
- type: recall_at_1
|
| 1390 |
+
value: 17.948
|
| 1391 |
+
- type: recall_at_10
|
| 1392 |
+
value: 45.062999999999995
|
| 1393 |
+
- type: recall_at_100
|
| 1394 |
+
value: 68.191
|
| 1395 |
+
- type: recall_at_1000
|
| 1396 |
+
value: 87.954
|
| 1397 |
+
- type: recall_at_3
|
| 1398 |
+
value: 31.112000000000002
|
| 1399 |
+
- type: recall_at_5
|
| 1400 |
+
value: 36.823
|
| 1401 |
+
- task:
|
| 1402 |
+
type: Retrieval
|
| 1403 |
+
dataset:
|
| 1404 |
+
type: hotpotqa
|
| 1405 |
+
name: MTEB HotpotQA
|
| 1406 |
+
config: default
|
| 1407 |
+
split: test
|
| 1408 |
+
revision: None
|
| 1409 |
+
metrics:
|
| 1410 |
+
- type: map_at_1
|
| 1411 |
+
value: 36.644
|
| 1412 |
+
- type: map_at_10
|
| 1413 |
+
value: 57.658
|
| 1414 |
+
- type: map_at_100
|
| 1415 |
+
value: 58.562000000000005
|
| 1416 |
+
- type: map_at_1000
|
| 1417 |
+
value: 58.62500000000001
|
| 1418 |
+
- type: map_at_3
|
| 1419 |
+
value: 54.022999999999996
|
| 1420 |
+
- type: map_at_5
|
| 1421 |
+
value: 56.293000000000006
|
| 1422 |
+
- type: mrr_at_1
|
| 1423 |
+
value: 73.288
|
| 1424 |
+
- type: mrr_at_10
|
| 1425 |
+
value: 80.51700000000001
|
| 1426 |
+
- type: mrr_at_100
|
| 1427 |
+
value: 80.72
|
| 1428 |
+
- type: mrr_at_1000
|
| 1429 |
+
value: 80.728
|
| 1430 |
+
- type: mrr_at_3
|
| 1431 |
+
value: 79.33200000000001
|
| 1432 |
+
- type: mrr_at_5
|
| 1433 |
+
value: 80.085
|
| 1434 |
+
- type: ndcg_at_1
|
| 1435 |
+
value: 73.288
|
| 1436 |
+
- type: ndcg_at_10
|
| 1437 |
+
value: 66.61
|
| 1438 |
+
- type: ndcg_at_100
|
| 1439 |
+
value: 69.723
|
| 1440 |
+
- type: ndcg_at_1000
|
| 1441 |
+
value: 70.96000000000001
|
| 1442 |
+
- type: ndcg_at_3
|
| 1443 |
+
value: 61.358999999999995
|
| 1444 |
+
- type: ndcg_at_5
|
| 1445 |
+
value: 64.277
|
| 1446 |
+
- type: precision_at_1
|
| 1447 |
+
value: 73.288
|
| 1448 |
+
- type: precision_at_10
|
| 1449 |
+
value: 14.17
|
| 1450 |
+
- type: precision_at_100
|
| 1451 |
+
value: 1.659
|
| 1452 |
+
- type: precision_at_1000
|
| 1453 |
+
value: 0.182
|
| 1454 |
+
- type: precision_at_3
|
| 1455 |
+
value: 39.487
|
| 1456 |
+
- type: precision_at_5
|
| 1457 |
+
value: 25.999
|
| 1458 |
+
- type: recall_at_1
|
| 1459 |
+
value: 36.644
|
| 1460 |
+
- type: recall_at_10
|
| 1461 |
+
value: 70.851
|
| 1462 |
+
- type: recall_at_100
|
| 1463 |
+
value: 82.94399999999999
|
| 1464 |
+
- type: recall_at_1000
|
| 1465 |
+
value: 91.134
|
| 1466 |
+
- type: recall_at_3
|
| 1467 |
+
value: 59.230000000000004
|
| 1468 |
+
- type: recall_at_5
|
| 1469 |
+
value: 64.997
|
| 1470 |
+
- task:
|
| 1471 |
+
type: Classification
|
| 1472 |
+
dataset:
|
| 1473 |
+
type: mteb/imdb
|
| 1474 |
+
name: MTEB ImdbClassification
|
| 1475 |
+
config: default
|
| 1476 |
+
split: test
|
| 1477 |
+
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
| 1478 |
+
metrics:
|
| 1479 |
+
- type: accuracy
|
| 1480 |
+
value: 86.00280000000001
|
| 1481 |
+
- type: ap
|
| 1482 |
+
value: 80.46302061021223
|
| 1483 |
+
- type: f1
|
| 1484 |
+
value: 85.9592921596419
|
| 1485 |
+
- task:
|
| 1486 |
+
type: Retrieval
|
| 1487 |
+
dataset:
|
| 1488 |
+
type: msmarco
|
| 1489 |
+
name: MTEB MSMARCO
|
| 1490 |
+
config: default
|
| 1491 |
+
split: dev
|
| 1492 |
+
revision: None
|
| 1493 |
+
metrics:
|
| 1494 |
+
- type: map_at_1
|
| 1495 |
+
value: 22.541
|
| 1496 |
+
- type: map_at_10
|
| 1497 |
+
value: 34.625
|
| 1498 |
+
- type: map_at_100
|
| 1499 |
+
value: 35.785
|
| 1500 |
+
- type: map_at_1000
|
| 1501 |
+
value: 35.831
|
| 1502 |
+
- type: map_at_3
|
| 1503 |
+
value: 30.823
|
| 1504 |
+
- type: map_at_5
|
| 1505 |
+
value: 32.967999999999996
|
| 1506 |
+
- type: mrr_at_1
|
| 1507 |
+
value: 23.180999999999997
|
| 1508 |
+
- type: mrr_at_10
|
| 1509 |
+
value: 35.207
|
| 1510 |
+
- type: mrr_at_100
|
| 1511 |
+
value: 36.315
|
| 1512 |
+
- type: mrr_at_1000
|
| 1513 |
+
value: 36.355
|
| 1514 |
+
- type: mrr_at_3
|
| 1515 |
+
value: 31.483
|
| 1516 |
+
- type: mrr_at_5
|
| 1517 |
+
value: 33.589999999999996
|
| 1518 |
+
- type: ndcg_at_1
|
| 1519 |
+
value: 23.195
|
| 1520 |
+
- type: ndcg_at_10
|
| 1521 |
+
value: 41.461
|
| 1522 |
+
- type: ndcg_at_100
|
| 1523 |
+
value: 47.032000000000004
|
| 1524 |
+
- type: ndcg_at_1000
|
| 1525 |
+
value: 48.199999999999996
|
| 1526 |
+
- type: ndcg_at_3
|
| 1527 |
+
value: 33.702
|
| 1528 |
+
- type: ndcg_at_5
|
| 1529 |
+
value: 37.522
|
| 1530 |
+
- type: precision_at_1
|
| 1531 |
+
value: 23.195
|
| 1532 |
+
- type: precision_at_10
|
| 1533 |
+
value: 6.526999999999999
|
| 1534 |
+
- type: precision_at_100
|
| 1535 |
+
value: 0.932
|
| 1536 |
+
- type: precision_at_1000
|
| 1537 |
+
value: 0.10300000000000001
|
| 1538 |
+
- type: precision_at_3
|
| 1539 |
+
value: 14.308000000000002
|
| 1540 |
+
- type: precision_at_5
|
| 1541 |
+
value: 10.507
|
| 1542 |
+
- type: recall_at_1
|
| 1543 |
+
value: 22.541
|
| 1544 |
+
- type: recall_at_10
|
| 1545 |
+
value: 62.524
|
| 1546 |
+
- type: recall_at_100
|
| 1547 |
+
value: 88.228
|
| 1548 |
+
- type: recall_at_1000
|
| 1549 |
+
value: 97.243
|
| 1550 |
+
- type: recall_at_3
|
| 1551 |
+
value: 41.38
|
| 1552 |
+
- type: recall_at_5
|
| 1553 |
+
value: 50.55
|
| 1554 |
+
- task:
|
| 1555 |
+
type: Classification
|
| 1556 |
+
dataset:
|
| 1557 |
+
type: mteb/mtop_domain
|
| 1558 |
+
name: MTEB MTOPDomainClassification (en)
|
| 1559 |
+
config: en
|
| 1560 |
+
split: test
|
| 1561 |
+
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
| 1562 |
+
metrics:
|
| 1563 |
+
- type: accuracy
|
| 1564 |
+
value: 92.69949840401279
|
| 1565 |
+
- type: f1
|
| 1566 |
+
value: 92.54141471311786
|
| 1567 |
+
- task:
|
| 1568 |
+
type: Classification
|
| 1569 |
+
dataset:
|
| 1570 |
+
type: mteb/mtop_intent
|
| 1571 |
+
name: MTEB MTOPIntentClassification (en)
|
| 1572 |
+
config: en
|
| 1573 |
+
split: test
|
| 1574 |
+
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
| 1575 |
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metrics:
|
| 1576 |
+
- type: accuracy
|
| 1577 |
+
value: 72.56041951664386
|
| 1578 |
+
- type: f1
|
| 1579 |
+
value: 55.88499977508287
|
| 1580 |
+
- task:
|
| 1581 |
+
type: Classification
|
| 1582 |
+
dataset:
|
| 1583 |
+
type: mteb/amazon_massive_intent
|
| 1584 |
+
name: MTEB MassiveIntentClassification (en)
|
| 1585 |
+
config: en
|
| 1586 |
+
split: test
|
| 1587 |
+
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
| 1588 |
+
metrics:
|
| 1589 |
+
- type: accuracy
|
| 1590 |
+
value: 71.62071284465365
|
| 1591 |
+
- type: f1
|
| 1592 |
+
value: 69.36717546572152
|
| 1593 |
+
- task:
|
| 1594 |
+
type: Classification
|
| 1595 |
+
dataset:
|
| 1596 |
+
type: mteb/amazon_massive_scenario
|
| 1597 |
+
name: MTEB MassiveScenarioClassification (en)
|
| 1598 |
+
config: en
|
| 1599 |
+
split: test
|
| 1600 |
+
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
| 1601 |
+
metrics:
|
| 1602 |
+
- type: accuracy
|
| 1603 |
+
value: 76.35843981170142
|
| 1604 |
+
- type: f1
|
| 1605 |
+
value: 76.15496453538884
|
| 1606 |
+
- task:
|
| 1607 |
+
type: Clustering
|
| 1608 |
+
dataset:
|
| 1609 |
+
type: mteb/medrxiv-clustering-p2p
|
| 1610 |
+
name: MTEB MedrxivClusteringP2P
|
| 1611 |
+
config: default
|
| 1612 |
+
split: test
|
| 1613 |
+
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
| 1614 |
+
metrics:
|
| 1615 |
+
- type: v_measure
|
| 1616 |
+
value: 31.33664956793118
|
| 1617 |
+
- task:
|
| 1618 |
+
type: Clustering
|
| 1619 |
+
dataset:
|
| 1620 |
+
type: mteb/medrxiv-clustering-s2s
|
| 1621 |
+
name: MTEB MedrxivClusteringS2S
|
| 1622 |
+
config: default
|
| 1623 |
+
split: test
|
| 1624 |
+
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
| 1625 |
+
metrics:
|
| 1626 |
+
- type: v_measure
|
| 1627 |
+
value: 27.883839621715524
|
| 1628 |
+
- task:
|
| 1629 |
+
type: Reranking
|
| 1630 |
+
dataset:
|
| 1631 |
+
type: mteb/mind_small
|
| 1632 |
+
name: MTEB MindSmallReranking
|
| 1633 |
+
config: default
|
| 1634 |
+
split: test
|
| 1635 |
+
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
| 1636 |
+
metrics:
|
| 1637 |
+
- type: map
|
| 1638 |
+
value: 30.096874986740758
|
| 1639 |
+
- type: mrr
|
| 1640 |
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value: 30.97300481932132
|
| 1641 |
+
- task:
|
| 1642 |
+
type: Retrieval
|
| 1643 |
+
dataset:
|
| 1644 |
+
type: nfcorpus
|
| 1645 |
+
name: MTEB NFCorpus
|
| 1646 |
+
config: default
|
| 1647 |
+
split: test
|
| 1648 |
+
revision: None
|
| 1649 |
+
metrics:
|
| 1650 |
+
- type: map_at_1
|
| 1651 |
+
value: 5.4
|
| 1652 |
+
- type: map_at_10
|
| 1653 |
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value: 11.852
|
| 1654 |
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- type: map_at_100
|
| 1655 |
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value: 14.758
|
| 1656 |
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- type: map_at_1000
|
| 1657 |
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value: 16.134
|
| 1658 |
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- type: map_at_3
|
| 1659 |
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value: 8.558
|
| 1660 |
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- type: map_at_5
|
| 1661 |
+
value: 10.087
|
| 1662 |
+
- type: mrr_at_1
|
| 1663 |
+
value: 44.272
|
| 1664 |
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- type: mrr_at_10
|
| 1665 |
+
value: 52.05800000000001
|
| 1666 |
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- type: mrr_at_100
|
| 1667 |
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value: 52.689
|
| 1668 |
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- type: mrr_at_1000
|
| 1669 |
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value: 52.742999999999995
|
| 1670 |
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- type: mrr_at_3
|
| 1671 |
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value: 50.205999999999996
|
| 1672 |
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- type: mrr_at_5
|
| 1673 |
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value: 51.367
|
| 1674 |
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- type: ndcg_at_1
|
| 1675 |
+
value: 42.57
|
| 1676 |
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- type: ndcg_at_10
|
| 1677 |
+
value: 32.449
|
| 1678 |
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- type: ndcg_at_100
|
| 1679 |
+
value: 29.596
|
| 1680 |
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- type: ndcg_at_1000
|
| 1681 |
+
value: 38.351
|
| 1682 |
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- type: ndcg_at_3
|
| 1683 |
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value: 37.044
|
| 1684 |
+
- type: ndcg_at_5
|
| 1685 |
+
value: 35.275
|
| 1686 |
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- type: precision_at_1
|
| 1687 |
+
value: 44.272
|
| 1688 |
+
- type: precision_at_10
|
| 1689 |
+
value: 23.87
|
| 1690 |
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- type: precision_at_100
|
| 1691 |
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value: 7.625
|
| 1692 |
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- type: precision_at_1000
|
| 1693 |
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value: 2.045
|
| 1694 |
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- type: precision_at_3
|
| 1695 |
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value: 34.365
|
| 1696 |
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- type: precision_at_5
|
| 1697 |
+
value: 30.341
|
| 1698 |
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- type: recall_at_1
|
| 1699 |
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value: 5.4
|
| 1700 |
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- type: recall_at_10
|
| 1701 |
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value: 15.943999999999999
|
| 1702 |
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- type: recall_at_100
|
| 1703 |
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value: 29.805
|
| 1704 |
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- type: recall_at_1000
|
| 1705 |
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value: 61.695
|
| 1706 |
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- type: recall_at_3
|
| 1707 |
+
value: 9.539
|
| 1708 |
+
- type: recall_at_5
|
| 1709 |
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value: 12.127
|
| 1710 |
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- task:
|
| 1711 |
+
type: Retrieval
|
| 1712 |
+
dataset:
|
| 1713 |
+
type: nq
|
| 1714 |
+
name: MTEB NQ
|
| 1715 |
+
config: default
|
| 1716 |
+
split: test
|
| 1717 |
+
revision: None
|
| 1718 |
+
metrics:
|
| 1719 |
+
- type: map_at_1
|
| 1720 |
+
value: 36.047000000000004
|
| 1721 |
+
- type: map_at_10
|
| 1722 |
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value: 51.6
|
| 1723 |
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- type: map_at_100
|
| 1724 |
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value: 52.449999999999996
|
| 1725 |
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- type: map_at_1000
|
| 1726 |
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value: 52.476
|
| 1727 |
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- type: map_at_3
|
| 1728 |
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value: 47.452
|
| 1729 |
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- type: map_at_5
|
| 1730 |
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value: 49.964
|
| 1731 |
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- type: mrr_at_1
|
| 1732 |
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value: 40.382
|
| 1733 |
+
- type: mrr_at_10
|
| 1734 |
+
value: 54.273
|
| 1735 |
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- type: mrr_at_100
|
| 1736 |
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value: 54.859
|
| 1737 |
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- type: mrr_at_1000
|
| 1738 |
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value: 54.876000000000005
|
| 1739 |
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- type: mrr_at_3
|
| 1740 |
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value: 51.014
|
| 1741 |
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- type: mrr_at_5
|
| 1742 |
+
value: 52.983999999999995
|
| 1743 |
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- type: ndcg_at_1
|
| 1744 |
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value: 40.353
|
| 1745 |
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- type: ndcg_at_10
|
| 1746 |
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value: 59.11300000000001
|
| 1747 |
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- type: ndcg_at_100
|
| 1748 |
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value: 62.604000000000006
|
| 1749 |
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- type: ndcg_at_1000
|
| 1750 |
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value: 63.187000000000005
|
| 1751 |
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- type: ndcg_at_3
|
| 1752 |
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value: 51.513
|
| 1753 |
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- type: ndcg_at_5
|
| 1754 |
+
value: 55.576
|
| 1755 |
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- type: precision_at_1
|
| 1756 |
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value: 40.353
|
| 1757 |
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- type: precision_at_10
|
| 1758 |
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value: 9.418
|
| 1759 |
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- type: precision_at_100
|
| 1760 |
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value: 1.1440000000000001
|
| 1761 |
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- type: precision_at_1000
|
| 1762 |
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value: 0.12
|
| 1763 |
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- type: precision_at_3
|
| 1764 |
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value: 23.078000000000003
|
| 1765 |
+
- type: precision_at_5
|
| 1766 |
+
value: 16.250999999999998
|
| 1767 |
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- type: recall_at_1
|
| 1768 |
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value: 36.047000000000004
|
| 1769 |
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- type: recall_at_10
|
| 1770 |
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value: 79.22200000000001
|
| 1771 |
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- type: recall_at_100
|
| 1772 |
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value: 94.23
|
| 1773 |
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- type: recall_at_1000
|
| 1774 |
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value: 98.51100000000001
|
| 1775 |
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- type: recall_at_3
|
| 1776 |
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value: 59.678
|
| 1777 |
+
- type: recall_at_5
|
| 1778 |
+
value: 68.967
|
| 1779 |
+
- task:
|
| 1780 |
+
type: Retrieval
|
| 1781 |
+
dataset:
|
| 1782 |
+
type: quora
|
| 1783 |
+
name: MTEB QuoraRetrieval
|
| 1784 |
+
config: default
|
| 1785 |
+
split: test
|
| 1786 |
+
revision: None
|
| 1787 |
+
metrics:
|
| 1788 |
+
- type: map_at_1
|
| 1789 |
+
value: 68.232
|
| 1790 |
+
- type: map_at_10
|
| 1791 |
+
value: 81.674
|
| 1792 |
+
- type: map_at_100
|
| 1793 |
+
value: 82.338
|
| 1794 |
+
- type: map_at_1000
|
| 1795 |
+
value: 82.36099999999999
|
| 1796 |
+
- type: map_at_3
|
| 1797 |
+
value: 78.833
|
| 1798 |
+
- type: map_at_5
|
| 1799 |
+
value: 80.58
|
| 1800 |
+
- type: mrr_at_1
|
| 1801 |
+
value: 78.64
|
| 1802 |
+
- type: mrr_at_10
|
| 1803 |
+
value: 85.164
|
| 1804 |
+
- type: mrr_at_100
|
| 1805 |
+
value: 85.317
|
| 1806 |
+
- type: mrr_at_1000
|
| 1807 |
+
value: 85.319
|
| 1808 |
+
- type: mrr_at_3
|
| 1809 |
+
value: 84.127
|
| 1810 |
+
- type: mrr_at_5
|
| 1811 |
+
value: 84.789
|
| 1812 |
+
- type: ndcg_at_1
|
| 1813 |
+
value: 78.63
|
| 1814 |
+
- type: ndcg_at_10
|
| 1815 |
+
value: 85.711
|
| 1816 |
+
- type: ndcg_at_100
|
| 1817 |
+
value: 87.238
|
| 1818 |
+
- type: ndcg_at_1000
|
| 1819 |
+
value: 87.444
|
| 1820 |
+
- type: ndcg_at_3
|
| 1821 |
+
value: 82.788
|
| 1822 |
+
- type: ndcg_at_5
|
| 1823 |
+
value: 84.313
|
| 1824 |
+
- type: precision_at_1
|
| 1825 |
+
value: 78.63
|
| 1826 |
+
- type: precision_at_10
|
| 1827 |
+
value: 12.977
|
| 1828 |
+
- type: precision_at_100
|
| 1829 |
+
value: 1.503
|
| 1830 |
+
- type: precision_at_1000
|
| 1831 |
+
value: 0.156
|
| 1832 |
+
- type: precision_at_3
|
| 1833 |
+
value: 36.113
|
| 1834 |
+
- type: precision_at_5
|
| 1835 |
+
value: 23.71
|
| 1836 |
+
- type: recall_at_1
|
| 1837 |
+
value: 68.232
|
| 1838 |
+
- type: recall_at_10
|
| 1839 |
+
value: 93.30199999999999
|
| 1840 |
+
- type: recall_at_100
|
| 1841 |
+
value: 98.799
|
| 1842 |
+
- type: recall_at_1000
|
| 1843 |
+
value: 99.885
|
| 1844 |
+
- type: recall_at_3
|
| 1845 |
+
value: 84.827
|
| 1846 |
+
- type: recall_at_5
|
| 1847 |
+
value: 89.188
|
| 1848 |
+
- task:
|
| 1849 |
+
type: Clustering
|
| 1850 |
+
dataset:
|
| 1851 |
+
type: mteb/reddit-clustering
|
| 1852 |
+
name: MTEB RedditClustering
|
| 1853 |
+
config: default
|
| 1854 |
+
split: test
|
| 1855 |
+
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
| 1856 |
+
metrics:
|
| 1857 |
+
- type: v_measure
|
| 1858 |
+
value: 45.71879170816294
|
| 1859 |
+
- task:
|
| 1860 |
+
type: Clustering
|
| 1861 |
+
dataset:
|
| 1862 |
+
type: mteb/reddit-clustering-p2p
|
| 1863 |
+
name: MTEB RedditClusteringP2P
|
| 1864 |
+
config: default
|
| 1865 |
+
split: test
|
| 1866 |
+
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
| 1867 |
+
metrics:
|
| 1868 |
+
- type: v_measure
|
| 1869 |
+
value: 59.65866311751794
|
| 1870 |
+
- task:
|
| 1871 |
+
type: Retrieval
|
| 1872 |
+
dataset:
|
| 1873 |
+
type: scidocs
|
| 1874 |
+
name: MTEB SCIDOCS
|
| 1875 |
+
config: default
|
| 1876 |
+
split: test
|
| 1877 |
+
revision: None
|
| 1878 |
+
metrics:
|
| 1879 |
+
- type: map_at_1
|
| 1880 |
+
value: 4.218
|
| 1881 |
+
- type: map_at_10
|
| 1882 |
+
value: 10.337
|
| 1883 |
+
- type: map_at_100
|
| 1884 |
+
value: 12.131
|
| 1885 |
+
- type: map_at_1000
|
| 1886 |
+
value: 12.411
|
| 1887 |
+
- type: map_at_3
|
| 1888 |
+
value: 7.4270000000000005
|
| 1889 |
+
- type: map_at_5
|
| 1890 |
+
value: 8.913
|
| 1891 |
+
- type: mrr_at_1
|
| 1892 |
+
value: 20.8
|
| 1893 |
+
- type: mrr_at_10
|
| 1894 |
+
value: 30.868000000000002
|
| 1895 |
+
- type: mrr_at_100
|
| 1896 |
+
value: 31.903
|
| 1897 |
+
- type: mrr_at_1000
|
| 1898 |
+
value: 31.972
|
| 1899 |
+
- type: mrr_at_3
|
| 1900 |
+
value: 27.367
|
| 1901 |
+
- type: mrr_at_5
|
| 1902 |
+
value: 29.372
|
| 1903 |
+
- type: ndcg_at_1
|
| 1904 |
+
value: 20.8
|
| 1905 |
+
- type: ndcg_at_10
|
| 1906 |
+
value: 17.765
|
| 1907 |
+
- type: ndcg_at_100
|
| 1908 |
+
value: 24.914
|
| 1909 |
+
- type: ndcg_at_1000
|
| 1910 |
+
value: 30.206
|
| 1911 |
+
- type: ndcg_at_3
|
| 1912 |
+
value: 16.64
|
| 1913 |
+
- type: ndcg_at_5
|
| 1914 |
+
value: 14.712
|
| 1915 |
+
- type: precision_at_1
|
| 1916 |
+
value: 20.8
|
| 1917 |
+
- type: precision_at_10
|
| 1918 |
+
value: 9.24
|
| 1919 |
+
- type: precision_at_100
|
| 1920 |
+
value: 1.9560000000000002
|
| 1921 |
+
- type: precision_at_1000
|
| 1922 |
+
value: 0.32299999999999995
|
| 1923 |
+
- type: precision_at_3
|
| 1924 |
+
value: 15.467
|
| 1925 |
+
- type: precision_at_5
|
| 1926 |
+
value: 12.94
|
| 1927 |
+
- type: recall_at_1
|
| 1928 |
+
value: 4.218
|
| 1929 |
+
- type: recall_at_10
|
| 1930 |
+
value: 18.752
|
| 1931 |
+
- type: recall_at_100
|
| 1932 |
+
value: 39.7
|
| 1933 |
+
- type: recall_at_1000
|
| 1934 |
+
value: 65.57300000000001
|
| 1935 |
+
- type: recall_at_3
|
| 1936 |
+
value: 9.428
|
| 1937 |
+
- type: recall_at_5
|
| 1938 |
+
value: 13.133000000000001
|
| 1939 |
+
- task:
|
| 1940 |
+
type: STS
|
| 1941 |
+
dataset:
|
| 1942 |
+
type: mteb/sickr-sts
|
| 1943 |
+
name: MTEB SICK-R
|
| 1944 |
+
config: default
|
| 1945 |
+
split: test
|
| 1946 |
+
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
| 1947 |
+
metrics:
|
| 1948 |
+
- type: cos_sim_pearson
|
| 1949 |
+
value: 83.04338850207233
|
| 1950 |
+
- type: cos_sim_spearman
|
| 1951 |
+
value: 78.5054651430423
|
| 1952 |
+
- type: euclidean_pearson
|
| 1953 |
+
value: 80.30739451228612
|
| 1954 |
+
- type: euclidean_spearman
|
| 1955 |
+
value: 78.48377464299097
|
| 1956 |
+
- type: manhattan_pearson
|
| 1957 |
+
value: 80.40795049052781
|
| 1958 |
+
- type: manhattan_spearman
|
| 1959 |
+
value: 78.49506205443114
|
| 1960 |
+
- task:
|
| 1961 |
+
type: STS
|
| 1962 |
+
dataset:
|
| 1963 |
+
type: mteb/sts12-sts
|
| 1964 |
+
name: MTEB STS12
|
| 1965 |
+
config: default
|
| 1966 |
+
split: test
|
| 1967 |
+
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
| 1968 |
+
metrics:
|
| 1969 |
+
- type: cos_sim_pearson
|
| 1970 |
+
value: 84.11596224442962
|
| 1971 |
+
- type: cos_sim_spearman
|
| 1972 |
+
value: 76.20997388935461
|
| 1973 |
+
- type: euclidean_pearson
|
| 1974 |
+
value: 80.56858451349109
|
| 1975 |
+
- type: euclidean_spearman
|
| 1976 |
+
value: 75.92659183871186
|
| 1977 |
+
- type: manhattan_pearson
|
| 1978 |
+
value: 80.60246102203844
|
| 1979 |
+
- type: manhattan_spearman
|
| 1980 |
+
value: 76.03018971432664
|
| 1981 |
+
- task:
|
| 1982 |
+
type: STS
|
| 1983 |
+
dataset:
|
| 1984 |
+
type: mteb/sts13-sts
|
| 1985 |
+
name: MTEB STS13
|
| 1986 |
+
config: default
|
| 1987 |
+
split: test
|
| 1988 |
+
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
| 1989 |
+
metrics:
|
| 1990 |
+
- type: cos_sim_pearson
|
| 1991 |
+
value: 81.34691640755737
|
| 1992 |
+
- type: cos_sim_spearman
|
| 1993 |
+
value: 82.4018369631579
|
| 1994 |
+
- type: euclidean_pearson
|
| 1995 |
+
value: 81.87673092245366
|
| 1996 |
+
- type: euclidean_spearman
|
| 1997 |
+
value: 82.3671489960678
|
| 1998 |
+
- type: manhattan_pearson
|
| 1999 |
+
value: 81.88222387719948
|
| 2000 |
+
- type: manhattan_spearman
|
| 2001 |
+
value: 82.3816590344736
|
| 2002 |
+
- task:
|
| 2003 |
+
type: STS
|
| 2004 |
+
dataset:
|
| 2005 |
+
type: mteb/sts14-sts
|
| 2006 |
+
name: MTEB STS14
|
| 2007 |
+
config: default
|
| 2008 |
+
split: test
|
| 2009 |
+
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
| 2010 |
+
metrics:
|
| 2011 |
+
- type: cos_sim_pearson
|
| 2012 |
+
value: 81.2836092579524
|
| 2013 |
+
- type: cos_sim_spearman
|
| 2014 |
+
value: 78.99982781772064
|
| 2015 |
+
- type: euclidean_pearson
|
| 2016 |
+
value: 80.5184271010527
|
| 2017 |
+
- type: euclidean_spearman
|
| 2018 |
+
value: 78.89777392101904
|
| 2019 |
+
- type: manhattan_pearson
|
| 2020 |
+
value: 80.53585705018664
|
| 2021 |
+
- type: manhattan_spearman
|
| 2022 |
+
value: 78.92898405472994
|
| 2023 |
+
- task:
|
| 2024 |
+
type: STS
|
| 2025 |
+
dataset:
|
| 2026 |
+
type: mteb/sts15-sts
|
| 2027 |
+
name: MTEB STS15
|
| 2028 |
+
config: default
|
| 2029 |
+
split: test
|
| 2030 |
+
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
| 2031 |
+
metrics:
|
| 2032 |
+
- type: cos_sim_pearson
|
| 2033 |
+
value: 86.7349907750784
|
| 2034 |
+
- type: cos_sim_spearman
|
| 2035 |
+
value: 87.7611234446225
|
| 2036 |
+
- type: euclidean_pearson
|
| 2037 |
+
value: 86.98759326731624
|
| 2038 |
+
- type: euclidean_spearman
|
| 2039 |
+
value: 87.58321319424618
|
| 2040 |
+
- type: manhattan_pearson
|
| 2041 |
+
value: 87.03483090370842
|
| 2042 |
+
- type: manhattan_spearman
|
| 2043 |
+
value: 87.63278333060288
|
| 2044 |
+
- task:
|
| 2045 |
+
type: STS
|
| 2046 |
+
dataset:
|
| 2047 |
+
type: mteb/sts16-sts
|
| 2048 |
+
name: MTEB STS16
|
| 2049 |
+
config: default
|
| 2050 |
+
split: test
|
| 2051 |
+
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
| 2052 |
+
metrics:
|
| 2053 |
+
- type: cos_sim_pearson
|
| 2054 |
+
value: 81.75873694924825
|
| 2055 |
+
- type: cos_sim_spearman
|
| 2056 |
+
value: 83.80237999094724
|
| 2057 |
+
- type: euclidean_pearson
|
| 2058 |
+
value: 83.55023725861537
|
| 2059 |
+
- type: euclidean_spearman
|
| 2060 |
+
value: 84.12744338577744
|
| 2061 |
+
- type: manhattan_pearson
|
| 2062 |
+
value: 83.58816983036232
|
| 2063 |
+
- type: manhattan_spearman
|
| 2064 |
+
value: 84.18520748676501
|
| 2065 |
+
- task:
|
| 2066 |
+
type: STS
|
| 2067 |
+
dataset:
|
| 2068 |
+
type: mteb/sts17-crosslingual-sts
|
| 2069 |
+
name: MTEB STS17 (en-en)
|
| 2070 |
+
config: en-en
|
| 2071 |
+
split: test
|
| 2072 |
+
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
| 2073 |
+
metrics:
|
| 2074 |
+
- type: cos_sim_pearson
|
| 2075 |
+
value: 87.21630882940174
|
| 2076 |
+
- type: cos_sim_spearman
|
| 2077 |
+
value: 87.72382883437031
|
| 2078 |
+
- type: euclidean_pearson
|
| 2079 |
+
value: 88.69933350930333
|
| 2080 |
+
- type: euclidean_spearman
|
| 2081 |
+
value: 88.24660814383081
|
| 2082 |
+
- type: manhattan_pearson
|
| 2083 |
+
value: 88.77331018833499
|
| 2084 |
+
- type: manhattan_spearman
|
| 2085 |
+
value: 88.26109989380632
|
| 2086 |
+
- task:
|
| 2087 |
+
type: STS
|
| 2088 |
+
dataset:
|
| 2089 |
+
type: mteb/sts22-crosslingual-sts
|
| 2090 |
+
name: MTEB STS22 (en)
|
| 2091 |
+
config: en
|
| 2092 |
+
split: test
|
| 2093 |
+
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
| 2094 |
+
metrics:
|
| 2095 |
+
- type: cos_sim_pearson
|
| 2096 |
+
value: 61.11854063060489
|
| 2097 |
+
- type: cos_sim_spearman
|
| 2098 |
+
value: 63.14678634195072
|
| 2099 |
+
- type: euclidean_pearson
|
| 2100 |
+
value: 61.679090067000864
|
| 2101 |
+
- type: euclidean_spearman
|
| 2102 |
+
value: 62.28876589509653
|
| 2103 |
+
- type: manhattan_pearson
|
| 2104 |
+
value: 62.082324165511004
|
| 2105 |
+
- type: manhattan_spearman
|
| 2106 |
+
value: 62.56030932816679
|
| 2107 |
+
- task:
|
| 2108 |
+
type: STS
|
| 2109 |
+
dataset:
|
| 2110 |
+
type: mteb/stsbenchmark-sts
|
| 2111 |
+
name: MTEB STSBenchmark
|
| 2112 |
+
config: default
|
| 2113 |
+
split: test
|
| 2114 |
+
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
| 2115 |
+
metrics:
|
| 2116 |
+
- type: cos_sim_pearson
|
| 2117 |
+
value: 84.00319882832645
|
| 2118 |
+
- type: cos_sim_spearman
|
| 2119 |
+
value: 85.94529772647257
|
| 2120 |
+
- type: euclidean_pearson
|
| 2121 |
+
value: 85.6661390122756
|
| 2122 |
+
- type: euclidean_spearman
|
| 2123 |
+
value: 85.97747815545827
|
| 2124 |
+
- type: manhattan_pearson
|
| 2125 |
+
value: 85.58422770541893
|
| 2126 |
+
- type: manhattan_spearman
|
| 2127 |
+
value: 85.9237139181532
|
| 2128 |
+
- task:
|
| 2129 |
+
type: Reranking
|
| 2130 |
+
dataset:
|
| 2131 |
+
type: mteb/scidocs-reranking
|
| 2132 |
+
name: MTEB SciDocsRR
|
| 2133 |
+
config: default
|
| 2134 |
+
split: test
|
| 2135 |
+
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
| 2136 |
+
metrics:
|
| 2137 |
+
- type: map
|
| 2138 |
+
value: 79.16198731863916
|
| 2139 |
+
- type: mrr
|
| 2140 |
+
value: 94.25202702163487
|
| 2141 |
+
- task:
|
| 2142 |
+
type: Retrieval
|
| 2143 |
+
dataset:
|
| 2144 |
+
type: scifact
|
| 2145 |
+
name: MTEB SciFact
|
| 2146 |
+
config: default
|
| 2147 |
+
split: test
|
| 2148 |
+
revision: None
|
| 2149 |
+
metrics:
|
| 2150 |
+
- type: map_at_1
|
| 2151 |
+
value: 54.761
|
| 2152 |
+
- type: map_at_10
|
| 2153 |
+
value: 64.396
|
| 2154 |
+
- type: map_at_100
|
| 2155 |
+
value: 65.07
|
| 2156 |
+
- type: map_at_1000
|
| 2157 |
+
value: 65.09899999999999
|
| 2158 |
+
- type: map_at_3
|
| 2159 |
+
value: 61.846000000000004
|
| 2160 |
+
- type: map_at_5
|
| 2161 |
+
value: 63.284
|
| 2162 |
+
- type: mrr_at_1
|
| 2163 |
+
value: 57.667
|
| 2164 |
+
- type: mrr_at_10
|
| 2165 |
+
value: 65.83099999999999
|
| 2166 |
+
- type: mrr_at_100
|
| 2167 |
+
value: 66.36800000000001
|
| 2168 |
+
- type: mrr_at_1000
|
| 2169 |
+
value: 66.39399999999999
|
| 2170 |
+
- type: mrr_at_3
|
| 2171 |
+
value: 64.056
|
| 2172 |
+
- type: mrr_at_5
|
| 2173 |
+
value: 65.206
|
| 2174 |
+
- type: ndcg_at_1
|
| 2175 |
+
value: 57.667
|
| 2176 |
+
- type: ndcg_at_10
|
| 2177 |
+
value: 68.854
|
| 2178 |
+
- type: ndcg_at_100
|
| 2179 |
+
value: 71.59100000000001
|
| 2180 |
+
- type: ndcg_at_1000
|
| 2181 |
+
value: 72.383
|
| 2182 |
+
- type: ndcg_at_3
|
| 2183 |
+
value: 64.671
|
| 2184 |
+
- type: ndcg_at_5
|
| 2185 |
+
value: 66.796
|
| 2186 |
+
- type: precision_at_1
|
| 2187 |
+
value: 57.667
|
| 2188 |
+
- type: precision_at_10
|
| 2189 |
+
value: 9.167
|
| 2190 |
+
- type: precision_at_100
|
| 2191 |
+
value: 1.053
|
| 2192 |
+
- type: precision_at_1000
|
| 2193 |
+
value: 0.11199999999999999
|
| 2194 |
+
- type: precision_at_3
|
| 2195 |
+
value: 25.444
|
| 2196 |
+
- type: precision_at_5
|
| 2197 |
+
value: 16.667
|
| 2198 |
+
- type: recall_at_1
|
| 2199 |
+
value: 54.761
|
| 2200 |
+
- type: recall_at_10
|
| 2201 |
+
value: 80.9
|
| 2202 |
+
- type: recall_at_100
|
| 2203 |
+
value: 92.767
|
| 2204 |
+
- type: recall_at_1000
|
| 2205 |
+
value: 99
|
| 2206 |
+
- type: recall_at_3
|
| 2207 |
+
value: 69.672
|
| 2208 |
+
- type: recall_at_5
|
| 2209 |
+
value: 75.083
|
| 2210 |
+
- task:
|
| 2211 |
+
type: PairClassification
|
| 2212 |
+
dataset:
|
| 2213 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
| 2214 |
+
name: MTEB SprintDuplicateQuestions
|
| 2215 |
+
config: default
|
| 2216 |
+
split: test
|
| 2217 |
+
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
| 2218 |
+
metrics:
|
| 2219 |
+
- type: cos_sim_accuracy
|
| 2220 |
+
value: 99.8079207920792
|
| 2221 |
+
- type: cos_sim_ap
|
| 2222 |
+
value: 94.88470927617445
|
| 2223 |
+
- type: cos_sim_f1
|
| 2224 |
+
value: 90.08179959100204
|
| 2225 |
+
- type: cos_sim_precision
|
| 2226 |
+
value: 92.15481171548117
|
| 2227 |
+
- type: cos_sim_recall
|
| 2228 |
+
value: 88.1
|
| 2229 |
+
- type: dot_accuracy
|
| 2230 |
+
value: 99.58613861386138
|
| 2231 |
+
- type: dot_ap
|
| 2232 |
+
value: 82.94822578881316
|
| 2233 |
+
- type: dot_f1
|
| 2234 |
+
value: 77.33333333333333
|
| 2235 |
+
- type: dot_precision
|
| 2236 |
+
value: 79.36842105263158
|
| 2237 |
+
- type: dot_recall
|
| 2238 |
+
value: 75.4
|
| 2239 |
+
- type: euclidean_accuracy
|
| 2240 |
+
value: 99.8069306930693
|
| 2241 |
+
- type: euclidean_ap
|
| 2242 |
+
value: 94.81367858031837
|
| 2243 |
+
- type: euclidean_f1
|
| 2244 |
+
value: 90.01009081735621
|
| 2245 |
+
- type: euclidean_precision
|
| 2246 |
+
value: 90.83503054989816
|
| 2247 |
+
- type: euclidean_recall
|
| 2248 |
+
value: 89.2
|
| 2249 |
+
- type: manhattan_accuracy
|
| 2250 |
+
value: 99.81188118811882
|
| 2251 |
+
- type: manhattan_ap
|
| 2252 |
+
value: 94.91405337220161
|
| 2253 |
+
- type: manhattan_f1
|
| 2254 |
+
value: 90.2763561924258
|
| 2255 |
+
- type: manhattan_precision
|
| 2256 |
+
value: 92.45283018867924
|
| 2257 |
+
- type: manhattan_recall
|
| 2258 |
+
value: 88.2
|
| 2259 |
+
- type: max_accuracy
|
| 2260 |
+
value: 99.81188118811882
|
| 2261 |
+
- type: max_ap
|
| 2262 |
+
value: 94.91405337220161
|
| 2263 |
+
- type: max_f1
|
| 2264 |
+
value: 90.2763561924258
|
| 2265 |
+
- task:
|
| 2266 |
+
type: Clustering
|
| 2267 |
+
dataset:
|
| 2268 |
+
type: mteb/stackexchange-clustering
|
| 2269 |
+
name: MTEB StackExchangeClustering
|
| 2270 |
+
config: default
|
| 2271 |
+
split: test
|
| 2272 |
+
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
| 2273 |
+
metrics:
|
| 2274 |
+
- type: v_measure
|
| 2275 |
+
value: 58.511599500053094
|
| 2276 |
+
- task:
|
| 2277 |
+
type: Clustering
|
| 2278 |
+
dataset:
|
| 2279 |
+
type: mteb/stackexchange-clustering-p2p
|
| 2280 |
+
name: MTEB StackExchangeClusteringP2P
|
| 2281 |
+
config: default
|
| 2282 |
+
split: test
|
| 2283 |
+
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
| 2284 |
+
metrics:
|
| 2285 |
+
- type: v_measure
|
| 2286 |
+
value: 31.984728147814707
|
| 2287 |
+
- task:
|
| 2288 |
+
type: Reranking
|
| 2289 |
+
dataset:
|
| 2290 |
+
type: mteb/stackoverflowdupquestions-reranking
|
| 2291 |
+
name: MTEB StackOverflowDupQuestions
|
| 2292 |
+
config: default
|
| 2293 |
+
split: test
|
| 2294 |
+
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
| 2295 |
+
metrics:
|
| 2296 |
+
- type: map
|
| 2297 |
+
value: 49.93428193939015
|
| 2298 |
+
- type: mrr
|
| 2299 |
+
value: 50.916557911043206
|
| 2300 |
+
- task:
|
| 2301 |
+
type: Summarization
|
| 2302 |
+
dataset:
|
| 2303 |
+
type: mteb/summeval
|
| 2304 |
+
name: MTEB SummEval
|
| 2305 |
+
config: default
|
| 2306 |
+
split: test
|
| 2307 |
+
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
| 2308 |
+
metrics:
|
| 2309 |
+
- type: cos_sim_pearson
|
| 2310 |
+
value: 31.562500894537145
|
| 2311 |
+
- type: cos_sim_spearman
|
| 2312 |
+
value: 31.162587976726307
|
| 2313 |
+
- type: dot_pearson
|
| 2314 |
+
value: 22.633662187735762
|
| 2315 |
+
- type: dot_spearman
|
| 2316 |
+
value: 22.723000282378962
|
| 2317 |
+
- task:
|
| 2318 |
+
type: Retrieval
|
| 2319 |
+
dataset:
|
| 2320 |
+
type: trec-covid
|
| 2321 |
+
name: MTEB TRECCOVID
|
| 2322 |
+
config: default
|
| 2323 |
+
split: test
|
| 2324 |
+
revision: None
|
| 2325 |
+
metrics:
|
| 2326 |
+
- type: map_at_1
|
| 2327 |
+
value: 0.219
|
| 2328 |
+
- type: map_at_10
|
| 2329 |
+
value: 1.871
|
| 2330 |
+
- type: map_at_100
|
| 2331 |
+
value: 10.487
|
| 2332 |
+
- type: map_at_1000
|
| 2333 |
+
value: 25.122
|
| 2334 |
+
- type: map_at_3
|
| 2335 |
+
value: 0.657
|
| 2336 |
+
- type: map_at_5
|
| 2337 |
+
value: 1.0699999999999998
|
| 2338 |
+
- type: mrr_at_1
|
| 2339 |
+
value: 84
|
| 2340 |
+
- type: mrr_at_10
|
| 2341 |
+
value: 89.567
|
| 2342 |
+
- type: mrr_at_100
|
| 2343 |
+
value: 89.748
|
| 2344 |
+
- type: mrr_at_1000
|
| 2345 |
+
value: 89.748
|
| 2346 |
+
- type: mrr_at_3
|
| 2347 |
+
value: 88.667
|
| 2348 |
+
- type: mrr_at_5
|
| 2349 |
+
value: 89.567
|
| 2350 |
+
- type: ndcg_at_1
|
| 2351 |
+
value: 80
|
| 2352 |
+
- type: ndcg_at_10
|
| 2353 |
+
value: 74.533
|
| 2354 |
+
- type: ndcg_at_100
|
| 2355 |
+
value: 55.839000000000006
|
| 2356 |
+
- type: ndcg_at_1000
|
| 2357 |
+
value: 49.748
|
| 2358 |
+
- type: ndcg_at_3
|
| 2359 |
+
value: 79.53099999999999
|
| 2360 |
+
- type: ndcg_at_5
|
| 2361 |
+
value: 78.245
|
| 2362 |
+
- type: precision_at_1
|
| 2363 |
+
value: 84
|
| 2364 |
+
- type: precision_at_10
|
| 2365 |
+
value: 78.4
|
| 2366 |
+
- type: precision_at_100
|
| 2367 |
+
value: 56.99999999999999
|
| 2368 |
+
- type: precision_at_1000
|
| 2369 |
+
value: 21.98
|
| 2370 |
+
- type: precision_at_3
|
| 2371 |
+
value: 85.333
|
| 2372 |
+
- type: precision_at_5
|
| 2373 |
+
value: 84.8
|
| 2374 |
+
- type: recall_at_1
|
| 2375 |
+
value: 0.219
|
| 2376 |
+
- type: recall_at_10
|
| 2377 |
+
value: 2.02
|
| 2378 |
+
- type: recall_at_100
|
| 2379 |
+
value: 13.555
|
| 2380 |
+
- type: recall_at_1000
|
| 2381 |
+
value: 46.739999999999995
|
| 2382 |
+
- type: recall_at_3
|
| 2383 |
+
value: 0.685
|
| 2384 |
+
- type: recall_at_5
|
| 2385 |
+
value: 1.13
|
| 2386 |
+
- task:
|
| 2387 |
+
type: Retrieval
|
| 2388 |
+
dataset:
|
| 2389 |
+
type: webis-touche2020
|
| 2390 |
+
name: MTEB Touche2020
|
| 2391 |
+
config: default
|
| 2392 |
+
split: test
|
| 2393 |
+
revision: None
|
| 2394 |
+
metrics:
|
| 2395 |
+
- type: map_at_1
|
| 2396 |
+
value: 3.5029999999999997
|
| 2397 |
+
- type: map_at_10
|
| 2398 |
+
value: 11.042
|
| 2399 |
+
- type: map_at_100
|
| 2400 |
+
value: 16.326999999999998
|
| 2401 |
+
- type: map_at_1000
|
| 2402 |
+
value: 17.836
|
| 2403 |
+
- type: map_at_3
|
| 2404 |
+
value: 6.174
|
| 2405 |
+
- type: map_at_5
|
| 2406 |
+
value: 7.979
|
| 2407 |
+
- type: mrr_at_1
|
| 2408 |
+
value: 42.857
|
| 2409 |
+
- type: mrr_at_10
|
| 2410 |
+
value: 52.617000000000004
|
| 2411 |
+
- type: mrr_at_100
|
| 2412 |
+
value: 53.351000000000006
|
| 2413 |
+
- type: mrr_at_1000
|
| 2414 |
+
value: 53.351000000000006
|
| 2415 |
+
- type: mrr_at_3
|
| 2416 |
+
value: 46.939
|
| 2417 |
+
- type: mrr_at_5
|
| 2418 |
+
value: 50.714000000000006
|
| 2419 |
+
- type: ndcg_at_1
|
| 2420 |
+
value: 38.775999999999996
|
| 2421 |
+
- type: ndcg_at_10
|
| 2422 |
+
value: 27.125
|
| 2423 |
+
- type: ndcg_at_100
|
| 2424 |
+
value: 35.845
|
| 2425 |
+
- type: ndcg_at_1000
|
| 2426 |
+
value: 47.377
|
| 2427 |
+
- type: ndcg_at_3
|
| 2428 |
+
value: 29.633
|
| 2429 |
+
- type: ndcg_at_5
|
| 2430 |
+
value: 28.378999999999998
|
| 2431 |
+
- type: precision_at_1
|
| 2432 |
+
value: 42.857
|
| 2433 |
+
- type: precision_at_10
|
| 2434 |
+
value: 24.082
|
| 2435 |
+
- type: precision_at_100
|
| 2436 |
+
value: 6.877999999999999
|
| 2437 |
+
- type: precision_at_1000
|
| 2438 |
+
value: 1.463
|
| 2439 |
+
- type: precision_at_3
|
| 2440 |
+
value: 29.932
|
| 2441 |
+
- type: precision_at_5
|
| 2442 |
+
value: 28.571
|
| 2443 |
+
- type: recall_at_1
|
| 2444 |
+
value: 3.5029999999999997
|
| 2445 |
+
- type: recall_at_10
|
| 2446 |
+
value: 17.068
|
| 2447 |
+
- type: recall_at_100
|
| 2448 |
+
value: 43.361
|
| 2449 |
+
- type: recall_at_1000
|
| 2450 |
+
value: 78.835
|
| 2451 |
+
- type: recall_at_3
|
| 2452 |
+
value: 6.821000000000001
|
| 2453 |
+
- type: recall_at_5
|
| 2454 |
+
value: 10.357
|
| 2455 |
+
- task:
|
| 2456 |
+
type: Classification
|
| 2457 |
+
dataset:
|
| 2458 |
+
type: mteb/toxic_conversations_50k
|
| 2459 |
+
name: MTEB ToxicConversationsClassification
|
| 2460 |
+
config: default
|
| 2461 |
+
split: test
|
| 2462 |
+
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
| 2463 |
+
metrics:
|
| 2464 |
+
- type: accuracy
|
| 2465 |
+
value: 71.0954
|
| 2466 |
+
- type: ap
|
| 2467 |
+
value: 14.216844153511959
|
| 2468 |
+
- type: f1
|
| 2469 |
+
value: 54.63687418565117
|
| 2470 |
+
- task:
|
| 2471 |
+
type: Classification
|
| 2472 |
+
dataset:
|
| 2473 |
+
type: mteb/tweet_sentiment_extraction
|
| 2474 |
+
name: MTEB TweetSentimentExtractionClassification
|
| 2475 |
+
config: default
|
| 2476 |
+
split: test
|
| 2477 |
+
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
| 2478 |
+
metrics:
|
| 2479 |
+
- type: accuracy
|
| 2480 |
+
value: 61.46293152235427
|
| 2481 |
+
- type: f1
|
| 2482 |
+
value: 61.744177921638645
|
| 2483 |
+
- task:
|
| 2484 |
+
type: Clustering
|
| 2485 |
+
dataset:
|
| 2486 |
+
type: mteb/twentynewsgroups-clustering
|
| 2487 |
+
name: MTEB TwentyNewsgroupsClustering
|
| 2488 |
+
config: default
|
| 2489 |
+
split: test
|
| 2490 |
+
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
| 2491 |
+
metrics:
|
| 2492 |
+
- type: v_measure
|
| 2493 |
+
value: 41.12708617788644
|
| 2494 |
+
- task:
|
| 2495 |
+
type: PairClassification
|
| 2496 |
+
dataset:
|
| 2497 |
+
type: mteb/twittersemeval2015-pairclassification
|
| 2498 |
+
name: MTEB TwitterSemEval2015
|
| 2499 |
+
config: default
|
| 2500 |
+
split: test
|
| 2501 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
| 2502 |
+
metrics:
|
| 2503 |
+
- type: cos_sim_accuracy
|
| 2504 |
+
value: 85.75430649102938
|
| 2505 |
+
- type: cos_sim_ap
|
| 2506 |
+
value: 73.34252536948081
|
| 2507 |
+
- type: cos_sim_f1
|
| 2508 |
+
value: 67.53758935173774
|
| 2509 |
+
- type: cos_sim_precision
|
| 2510 |
+
value: 63.3672525439408
|
| 2511 |
+
- type: cos_sim_recall
|
| 2512 |
+
value: 72.29551451187335
|
| 2513 |
+
- type: dot_accuracy
|
| 2514 |
+
value: 81.71305954580676
|
| 2515 |
+
- type: dot_ap
|
| 2516 |
+
value: 59.5532209082386
|
| 2517 |
+
- type: dot_f1
|
| 2518 |
+
value: 56.18466898954705
|
| 2519 |
+
- type: dot_precision
|
| 2520 |
+
value: 47.830923248053395
|
| 2521 |
+
- type: dot_recall
|
| 2522 |
+
value: 68.07387862796834
|
| 2523 |
+
- type: euclidean_accuracy
|
| 2524 |
+
value: 85.81987244441795
|
| 2525 |
+
- type: euclidean_ap
|
| 2526 |
+
value: 73.34325409809446
|
| 2527 |
+
- type: euclidean_f1
|
| 2528 |
+
value: 67.83451360417443
|
| 2529 |
+
- type: euclidean_precision
|
| 2530 |
+
value: 64.09955388588871
|
| 2531 |
+
- type: euclidean_recall
|
| 2532 |
+
value: 72.0316622691293
|
| 2533 |
+
- type: manhattan_accuracy
|
| 2534 |
+
value: 85.68277999642368
|
| 2535 |
+
- type: manhattan_ap
|
| 2536 |
+
value: 73.1535450121903
|
| 2537 |
+
- type: manhattan_f1
|
| 2538 |
+
value: 67.928237896289
|
| 2539 |
+
- type: manhattan_precision
|
| 2540 |
+
value: 63.56945722171113
|
| 2541 |
+
- type: manhattan_recall
|
| 2542 |
+
value: 72.9287598944591
|
| 2543 |
+
- type: max_accuracy
|
| 2544 |
+
value: 85.81987244441795
|
| 2545 |
+
- type: max_ap
|
| 2546 |
+
value: 73.34325409809446
|
| 2547 |
+
- type: max_f1
|
| 2548 |
+
value: 67.928237896289
|
| 2549 |
+
- task:
|
| 2550 |
+
type: PairClassification
|
| 2551 |
+
dataset:
|
| 2552 |
+
type: mteb/twitterurlcorpus-pairclassification
|
| 2553 |
+
name: MTEB TwitterURLCorpus
|
| 2554 |
+
config: default
|
| 2555 |
+
split: test
|
| 2556 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
| 2557 |
+
metrics:
|
| 2558 |
+
- type: cos_sim_accuracy
|
| 2559 |
+
value: 88.90441262079403
|
| 2560 |
+
- type: cos_sim_ap
|
| 2561 |
+
value: 85.79331880741438
|
| 2562 |
+
- type: cos_sim_f1
|
| 2563 |
+
value: 78.31563529842548
|
| 2564 |
+
- type: cos_sim_precision
|
| 2565 |
+
value: 74.6683424102779
|
| 2566 |
+
- type: cos_sim_recall
|
| 2567 |
+
value: 82.33754234678165
|
| 2568 |
+
- type: dot_accuracy
|
| 2569 |
+
value: 84.89928978926534
|
| 2570 |
+
- type: dot_ap
|
| 2571 |
+
value: 75.25819218316
|
| 2572 |
+
- type: dot_f1
|
| 2573 |
+
value: 69.88730119720536
|
| 2574 |
+
- type: dot_precision
|
| 2575 |
+
value: 64.23362374959665
|
| 2576 |
+
- type: dot_recall
|
| 2577 |
+
value: 76.63227594702803
|
| 2578 |
+
- type: euclidean_accuracy
|
| 2579 |
+
value: 89.01695967710637
|
| 2580 |
+
- type: euclidean_ap
|
| 2581 |
+
value: 85.98986606038852
|
| 2582 |
+
- type: euclidean_f1
|
| 2583 |
+
value: 78.5277880014722
|
| 2584 |
+
- type: euclidean_precision
|
| 2585 |
+
value: 75.22211253701876
|
| 2586 |
+
- type: euclidean_recall
|
| 2587 |
+
value: 82.13735756082538
|
| 2588 |
+
- type: manhattan_accuracy
|
| 2589 |
+
value: 88.99561454573679
|
| 2590 |
+
- type: manhattan_ap
|
| 2591 |
+
value: 85.92262421793953
|
| 2592 |
+
- type: manhattan_f1
|
| 2593 |
+
value: 78.38866094740769
|
| 2594 |
+
- type: manhattan_precision
|
| 2595 |
+
value: 76.02373028505282
|
| 2596 |
+
- type: manhattan_recall
|
| 2597 |
+
value: 80.9054511857099
|
| 2598 |
+
- type: max_accuracy
|
| 2599 |
+
value: 89.01695967710637
|
| 2600 |
+
- type: max_ap
|
| 2601 |
+
value: 85.98986606038852
|
| 2602 |
+
- type: max_f1
|
| 2603 |
+
value: 78.5277880014722
|
| 2604 |
+
---
|
| 2605 |
+
|
| 2606 |
+
# E5-small-v2
|
| 2607 |
+
|
| 2608 |
+
[Text Embeddings by Weakly-Supervised Contrastive Pre-training](https://arxiv.org/pdf/2212.03533.pdf).
|
| 2609 |
+
Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022
|
| 2610 |
+
|
| 2611 |
+
This model has 12 layers and the embedding size is 384.
|
| 2612 |
+
|
| 2613 |
+
## Usage
|
| 2614 |
+
|
| 2615 |
+
Below is an example to encode queries and passages from the MS-MARCO passage ranking dataset.
|
| 2616 |
+
|
| 2617 |
+
```python
|
| 2618 |
+
import torch.nn.functional as F
|
| 2619 |
+
|
| 2620 |
+
from torch import Tensor
|
| 2621 |
+
from transformers import AutoTokenizer, AutoModel
|
| 2622 |
+
|
| 2623 |
+
|
| 2624 |
+
def average_pool(last_hidden_states: Tensor,
|
| 2625 |
+
attention_mask: Tensor) -> Tensor:
|
| 2626 |
+
last_hidden = last_hidden_states.masked_fill(~attention_mask[..., None].bool(), 0.0)
|
| 2627 |
+
return last_hidden.sum(dim=1) / attention_mask.sum(dim=1)[..., None]
|
| 2628 |
+
|
| 2629 |
+
|
| 2630 |
+
# Each input text should start with "query: " or "passage: ".
|
| 2631 |
+
# For tasks other than retrieval, you can simply use the "query: " prefix.
|
| 2632 |
+
input_texts = ['query: how much protein should a female eat',
|
| 2633 |
+
'query: summit define',
|
| 2634 |
+
"passage: As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.",
|
| 2635 |
+
"passage: Definition of summit for English Language Learners. : 1 the highest point of a mountain : the top of a mountain. : 2 the highest level. : 3 a meeting or series of meetings between the leaders of two or more governments."]
|
| 2636 |
+
|
| 2637 |
+
tokenizer = AutoTokenizer.from_pretrained('ggrn/e5-small-v2')
|
| 2638 |
+
model = AutoModel.from_pretrained('ggrn/e5-small-v2')
|
| 2639 |
+
|
| 2640 |
+
# Tokenize the input texts
|
| 2641 |
+
batch_dict = tokenizer(input_texts, max_length=512, padding=True, truncation=True, return_tensors='pt')
|
| 2642 |
+
|
| 2643 |
+
outputs = model(**batch_dict)
|
| 2644 |
+
embeddings = average_pool(outputs.last_hidden_state, batch_dict['attention_mask'])
|
| 2645 |
+
|
| 2646 |
+
# (Optionally) normalize embeddings
|
| 2647 |
+
embeddings = F.normalize(embeddings, p=2, dim=1)
|
| 2648 |
+
scores = (embeddings[:2] @ embeddings[2:].T) * 100
|
| 2649 |
+
print(scores.tolist())
|
| 2650 |
+
```
|
| 2651 |
+
|
| 2652 |
+
## Training Details
|
| 2653 |
+
|
| 2654 |
+
Please refer to our paper at [https://arxiv.org/pdf/2212.03533.pdf](https://arxiv.org/pdf/2212.03533.pdf).
|
| 2655 |
+
|
| 2656 |
+
## Benchmark Evaluation
|
| 2657 |
+
|
| 2658 |
+
Check out [unilm/e5](https://github.com/microsoft/unilm/tree/master/e5) to reproduce evaluation results
|
| 2659 |
+
on the [BEIR](https://arxiv.org/abs/2104.08663) and [MTEB benchmark](https://arxiv.org/abs/2210.07316).
|
| 2660 |
+
|
| 2661 |
+
## Citation
|
| 2662 |
+
|
| 2663 |
+
If you find our paper or models helpful, please consider cite as follows:
|
| 2664 |
+
|
| 2665 |
+
```
|
| 2666 |
+
@article{wang2022text,
|
| 2667 |
+
title={Text Embeddings by Weakly-Supervised Contrastive Pre-training},
|
| 2668 |
+
author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Jiao, Binxing and Yang, Linjun and Jiang, Daxin and Majumder, Rangan and Wei, Furu},
|
| 2669 |
+
journal={arXiv preprint arXiv:2212.03533},
|
| 2670 |
+
year={2022}
|
| 2671 |
+
}
|
| 2672 |
+
```
|
| 2673 |
+
|
| 2674 |
+
## Limitations
|
| 2675 |
+
|
| 2676 |
+
This model only works for English texts. Long texts will be truncated to at most 512 tokens.
|
| 2677 |
+
|
| 2678 |
+
## Sentence Transformers
|
| 2679 |
+
|
| 2680 |
+
Below is an example for usage with sentence_transformers. `pip install sentence_transformers~=2.2.2`
|
| 2681 |
+
This is community contributed, and results may vary up to numerical precision.
|
| 2682 |
+
```python
|
| 2683 |
+
from sentence_transformers import SentenceTransformer
|
| 2684 |
+
model = SentenceTransformer('ggrn/e5-small-v2')
|
| 2685 |
+
embeddings = model.encode(input_texts, normalize_embeddings=True)
|
| 2686 |
+
```
|
e5-small-v2/config.json
ADDED
|
@@ -0,0 +1,25 @@
|
|
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|
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|
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|
|
|
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|
|
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|
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|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "tmp/",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"BertModel"
|
| 5 |
+
],
|
| 6 |
+
"attention_probs_dropout_prob": 0.1,
|
| 7 |
+
"classifier_dropout": null,
|
| 8 |
+
"hidden_act": "gelu",
|
| 9 |
+
"hidden_dropout_prob": 0.1,
|
| 10 |
+
"hidden_size": 384,
|
| 11 |
+
"initializer_range": 0.02,
|
| 12 |
+
"intermediate_size": 1536,
|
| 13 |
+
"layer_norm_eps": 1e-12,
|
| 14 |
+
"max_position_embeddings": 512,
|
| 15 |
+
"model_type": "bert",
|
| 16 |
+
"num_attention_heads": 12,
|
| 17 |
+
"num_hidden_layers": 12,
|
| 18 |
+
"pad_token_id": 0,
|
| 19 |
+
"position_embedding_type": "absolute",
|
| 20 |
+
"torch_dtype": "float32",
|
| 21 |
+
"transformers_version": "4.29.0.dev0",
|
| 22 |
+
"type_vocab_size": 2,
|
| 23 |
+
"use_cache": true,
|
| 24 |
+
"vocab_size": 30522
|
| 25 |
+
}
|
e5-small-v2/modules.json
ADDED
|
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[
|
| 2 |
+
{
|
| 3 |
+
"idx": 0,
|
| 4 |
+
"name": "0",
|
| 5 |
+
"path": "",
|
| 6 |
+
"type": "sentence_transformers.models.Transformer"
|
| 7 |
+
},
|
| 8 |
+
{
|
| 9 |
+
"idx": 1,
|
| 10 |
+
"name": "1",
|
| 11 |
+
"path": "1_Pooling",
|
| 12 |
+
"type": "sentence_transformers.models.Pooling"
|
| 13 |
+
},
|
| 14 |
+
{
|
| 15 |
+
"idx": 2,
|
| 16 |
+
"name": "2",
|
| 17 |
+
"path": "2_Normalize",
|
| 18 |
+
"type": "sentence_transformers.models.Normalize"
|
| 19 |
+
}
|
| 20 |
+
]
|
e5-small-v2/pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4790fed2919e70bff573d01cd3aede75970f219ab4c0b0aeadd0f4b98084a17d
|
| 3 |
+
size 133508397
|
e5-small-v2/sentence_bert_config.json
ADDED
|
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"max_seq_length": 512,
|
| 3 |
+
"do_lower_case": false
|
| 4 |
+
}
|
e5-small-v2/source.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
https://huggingface.co/ggrn/e5-small-v2
|
e5-small-v2/special_tokens_map.json
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"cls_token": "[CLS]",
|
| 3 |
+
"mask_token": "[MASK]",
|
| 4 |
+
"pad_token": "[PAD]",
|
| 5 |
+
"sep_token": "[SEP]",
|
| 6 |
+
"unk_token": "[UNK]"
|
| 7 |
+
}
|
e5-small-v2/tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
e5-small-v2/tokenizer_config.json
ADDED
|
@@ -0,0 +1,15 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"clean_up_tokenization_spaces": true,
|
| 3 |
+
"cls_token": "[CLS]",
|
| 4 |
+
"do_basic_tokenize": true,
|
| 5 |
+
"do_lower_case": true,
|
| 6 |
+
"mask_token": "[MASK]",
|
| 7 |
+
"model_max_length": 1000000000000000019884624838656,
|
| 8 |
+
"never_split": null,
|
| 9 |
+
"pad_token": "[PAD]",
|
| 10 |
+
"sep_token": "[SEP]",
|
| 11 |
+
"strip_accents": null,
|
| 12 |
+
"tokenize_chinese_chars": true,
|
| 13 |
+
"tokenizer_class": "BertTokenizer",
|
| 14 |
+
"unk_token": "[UNK]"
|
| 15 |
+
}
|