add msmarco results
Browse files* Add results
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* revert
* Rmv files
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* Add
* cleanup
* Add evals
* Add res
* Update model_meta.json
---------
Co-authored-by: Kenneth Enevoldsen <[email protected]>
- results/GritLM__GritLM-7B/13f00a0e36500c80ce12870ea513846a066004af/model_meta.json +1 -1
- results/Lajavaness__bilingual-embedding-base/0bfc54bb2aa2666dd84715289c7ef58a95eb4d8d/MSMARCO.json +456 -0
- results/Omartificial-Intelligence-Space__Arabic-mpnet-base-all-nli-triplet/2628cb641e040f44328195fadcdfb58e6d5cffa7/MSMARCO.json +456 -0
- results/deepvk__deberta-v1-base/bdd30b0e19757e6940c92c7aff19e8fc0a60dff4/MSMARCO.json +456 -0
- results/minishlab__M2V_base_glove/38ebd7f10f71e67fa8db898290f92b82e9cfff2b/MSMARCO.json +456 -0
- results/minishlab__M2V_base_glove_subword/5f4f5ca159b7321a8b39739bba0794fa0debddf4/MSMARCO.json +456 -0
- results/minishlab__M2V_base_output/02460ae401a22b09d2c6652e23371398329551e2/MSMARCO.json +456 -0
- results/minishlab__potion-base-2M/86db093558fbced2072b929eb1690bce5272bd4b/MSMARCO.json +456 -0
- results/minishlab__potion-base-4M/81b1802ada41afcd0987a37dc15e569c9fa76f04/MSMARCO.json +456 -0
- results/minishlab__potion-base-8M/dcbec7aa2d52fc76754ac6291803feedd8c619ce/MSMARCO.json +456 -0
- results/nomic-ai__nomic-embed-text-v1-ablated/7d948905c5d5d3874fa55a925d68e49dbf411e5f/model_meta.json +1 -1
results/GritLM__GritLM-7B/13f00a0e36500c80ce12870ea513846a066004af/model_meta.json
CHANGED
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-
{"name": "GritLM/GritLM-7B", "revision": "13f00a0e36500c80ce12870ea513846a066004af", "release_date": "2024-02-15", "languages": ["eng_Latn", "fra_Latn", "deu_Latn", "ita_Latn", "spa_Latn"], "n_parameters": 7240000000, "max_tokens": 4096.0, "embed_dim": 4096, "license": "apache-2.0", "open_weights": true, "public_training_code": "https://github.com/ContextualAI/gritlm", "framework": ["GritLM", "PyTorch"], "reference": "https://huggingface.co/GritLM/GritLM-7B", "similarity_fn_name": "cosine", "use_instructions": true, "training_datasets": {"MSMARCO": ["train"], "MSMARCOHardNegatives": ["train"], "NanoMSMARCORetrieval": ["train"], "MSMARCO-PL": ["train"], "NQ": ["train"], "NQHardNegatives": ["train"], "NanoNQRetrieval": ["train"], "NQ-PL": ["train"]}, "adapted_from": null, "superseded_by": null, "loader": "instruct_wrapper"}
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+
{"name": "GritLM/GritLM-7B", "revision": "13f00a0e36500c80ce12870ea513846a066004af", "release_date": "2024-02-15", "languages": ["eng_Latn", "fra_Latn", "deu_Latn", "ita_Latn", "spa_Latn"], "n_parameters": 7240000000, "max_tokens": 4096.0, "embed_dim": 4096, "license": "apache-2.0", "open_weights": true, "public_training_code": "https://github.com/ContextualAI/gritlm", "framework": ["GritLM", "PyTorch"], "reference": "https://huggingface.co/GritLM/GritLM-7B", "similarity_fn_name": "cosine", "use_instructions": true, "training_datasets": {"MSMARCO": ["train"], "MSMARCOHardNegatives": ["train"], "NanoMSMARCORetrieval": ["train"], "MSMARCO-PL": ["train"], "NQ": ["train"], "NQHardNegatives": ["train"], "NanoNQRetrieval": ["train"], "NQ-PL": ["train"]}, "adapted_from": null, "superseded_by": null, "loader": "instruct_wrapper"}
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results/Lajavaness__bilingual-embedding-base/0bfc54bb2aa2666dd84715289c7ef58a95eb4d8d/MSMARCO.json
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|
| 1 |
+
{
|
| 2 |
+
"dataset_revision": "c5a29a104738b98a9e76336939199e264163d4a0",
|
| 3 |
+
"task_name": "MSMARCO",
|
| 4 |
+
"mteb_version": "1.18.0",
|
| 5 |
+
"scores": {
|
| 6 |
+
"train": [
|
| 7 |
+
{
|
| 8 |
+
"ndcg_at_1": 0.17665,
|
| 9 |
+
"ndcg_at_3": 0.27065,
|
| 10 |
+
"ndcg_at_5": 0.30846,
|
| 11 |
+
"ndcg_at_10": 0.34774,
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| 12 |
+
"ndcg_at_20": 0.37538,
|
| 13 |
+
"ndcg_at_100": 0.41159,
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| 14 |
+
"ndcg_at_1000": 0.42721,
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| 15 |
+
"map_at_1": 0.17192,
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| 16 |
+
"map_at_3": 0.2451,
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| 17 |
+
"map_at_5": 0.26625,
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| 18 |
+
"map_at_10": 0.28271,
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| 19 |
+
"map_at_20": 0.29045,
|
| 20 |
+
"map_at_100": 0.29562,
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| 21 |
+
"map_at_1000": 0.29623,
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| 22 |
+
"recall_at_1": 0.17192,
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| 23 |
+
"recall_at_3": 0.33952,
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| 24 |
+
"recall_at_5": 0.43056,
|
| 25 |
+
"recall_at_10": 0.55035,
|
| 26 |
+
"recall_at_20": 0.65797,
|
| 27 |
+
"recall_at_100": 0.84931,
|
| 28 |
+
"recall_at_1000": 0.9695,
|
| 29 |
+
"precision_at_1": 0.17665,
|
| 30 |
+
"precision_at_3": 0.11695,
|
| 31 |
+
"precision_at_5": 0.08925,
|
| 32 |
+
"precision_at_10": 0.05725,
|
| 33 |
+
"precision_at_20": 0.03433,
|
| 34 |
+
"precision_at_100": 0.00892,
|
| 35 |
+
"precision_at_1000": 0.00102,
|
| 36 |
+
"mrr_at_1": 0.176677,
|
| 37 |
+
"mrr_at_3": 0.250286,
|
| 38 |
+
"mrr_at_5": 0.271211,
|
| 39 |
+
"mrr_at_10": 0.287374,
|
| 40 |
+
"mrr_at_20": 0.294909,
|
| 41 |
+
"mrr_at_100": 0.299848,
|
| 42 |
+
"mrr_at_1000": 0.300407,
|
| 43 |
+
"nauc_ndcg_at_1_max": -0.015441,
|
| 44 |
+
"nauc_ndcg_at_1_std": -0.114849,
|
| 45 |
+
"nauc_ndcg_at_1_diff1": 0.354993,
|
| 46 |
+
"nauc_ndcg_at_3_max": -0.017441,
|
| 47 |
+
"nauc_ndcg_at_3_std": -0.114218,
|
| 48 |
+
"nauc_ndcg_at_3_diff1": 0.31112,
|
| 49 |
+
"nauc_ndcg_at_5_max": -0.015318,
|
| 50 |
+
"nauc_ndcg_at_5_std": -0.106517,
|
| 51 |
+
"nauc_ndcg_at_5_diff1": 0.305562,
|
| 52 |
+
"nauc_ndcg_at_10_max": -0.011426,
|
| 53 |
+
"nauc_ndcg_at_10_std": -0.090435,
|
| 54 |
+
"nauc_ndcg_at_10_diff1": 0.30301,
|
| 55 |
+
"nauc_ndcg_at_20_max": -0.006661,
|
| 56 |
+
"nauc_ndcg_at_20_std": -0.071971,
|
| 57 |
+
"nauc_ndcg_at_20_diff1": 0.303025,
|
| 58 |
+
"nauc_ndcg_at_100_max": 0.000597,
|
| 59 |
+
"nauc_ndcg_at_100_std": -0.051827,
|
| 60 |
+
"nauc_ndcg_at_100_diff1": 0.30518,
|
| 61 |
+
"nauc_ndcg_at_1000_max": -0.001263,
|
| 62 |
+
"nauc_ndcg_at_1000_std": -0.06704,
|
| 63 |
+
"nauc_ndcg_at_1000_diff1": 0.30717,
|
| 64 |
+
"nauc_map_at_1_max": -0.016339,
|
| 65 |
+
"nauc_map_at_1_std": -0.114613,
|
| 66 |
+
"nauc_map_at_1_diff1": 0.357934,
|
| 67 |
+
"nauc_map_at_3_max": -0.017457,
|
| 68 |
+
"nauc_map_at_3_std": -0.114649,
|
| 69 |
+
"nauc_map_at_3_diff1": 0.320953,
|
| 70 |
+
"nauc_map_at_5_max": -0.016186,
|
| 71 |
+
"nauc_map_at_5_std": -0.110258,
|
| 72 |
+
"nauc_map_at_5_diff1": 0.317513,
|
| 73 |
+
"nauc_map_at_10_max": -0.014523,
|
| 74 |
+
"nauc_map_at_10_std": -0.103594,
|
| 75 |
+
"nauc_map_at_10_diff1": 0.316481,
|
| 76 |
+
"nauc_map_at_20_max": -0.013201,
|
| 77 |
+
"nauc_map_at_20_std": -0.098599,
|
| 78 |
+
"nauc_map_at_20_diff1": 0.316592,
|
| 79 |
+
"nauc_map_at_100_max": -0.012237,
|
| 80 |
+
"nauc_map_at_100_std": -0.095888,
|
| 81 |
+
"nauc_map_at_100_diff1": 0.316973,
|
| 82 |
+
"nauc_map_at_1000_max": -0.012266,
|
| 83 |
+
"nauc_map_at_1000_std": -0.096312,
|
| 84 |
+
"nauc_map_at_1000_diff1": 0.317046,
|
| 85 |
+
"nauc_recall_at_1_max": -0.016339,
|
| 86 |
+
"nauc_recall_at_1_std": -0.114613,
|
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| 453 |
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| 454 |
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|
results/Omartificial-Intelligence-Space__Arabic-mpnet-base-all-nli-triplet/2628cb641e040f44328195fadcdfb58e6d5cffa7/MSMARCO.json
ADDED
|
@@ -0,0 +1,456 @@
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|
| 1 |
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{
|
| 2 |
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"dataset_revision": "c5a29a104738b98a9e76336939199e264163d4a0",
|
| 3 |
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|
| 4 |
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|
| 5 |
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| 6 |
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| 449 |
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| 452 |
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| 453 |
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| 454 |
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}
|
results/deepvk__deberta-v1-base/bdd30b0e19757e6940c92c7aff19e8fc0a60dff4/MSMARCO.json
ADDED
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@@ -0,0 +1,456 @@
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|
results/minishlab__M2V_base_glove/38ebd7f10f71e67fa8db898290f92b82e9cfff2b/MSMARCO.json
ADDED
|
@@ -0,0 +1,456 @@
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}
|
results/minishlab__M2V_base_glove_subword/5f4f5ca159b7321a8b39739bba0794fa0debddf4/MSMARCO.json
ADDED
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|
results/minishlab__M2V_base_output/02460ae401a22b09d2c6652e23371398329551e2/MSMARCO.json
ADDED
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| 1 |
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| 435 |
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| 436 |
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| 437 |
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| 438 |
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| 439 |
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| 440 |
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| 441 |
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| 442 |
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| 443 |
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| 444 |
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|
| 445 |
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|
| 446 |
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|
| 447 |
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|
| 448 |
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"languages": [
|
| 449 |
+
"eng-Latn"
|
| 450 |
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]
|
| 451 |
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}
|
| 452 |
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]
|
| 453 |
+
},
|
| 454 |
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"evaluation_time": 68883.71420168877,
|
| 455 |
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"kg_co2_emissions": 9.911731867935014
|
| 456 |
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}
|
results/minishlab__potion-base-2M/86db093558fbced2072b929eb1690bce5272bd4b/MSMARCO.json
ADDED
|
@@ -0,0 +1,456 @@
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|
| 1 |
+
{
|
| 2 |
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"dataset_revision": "c5a29a104738b98a9e76336939199e264163d4a0",
|
| 3 |
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"task_name": "MSMARCO",
|
| 4 |
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"mteb_version": "1.18.0",
|
| 5 |
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"scores": {
|
| 6 |
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"train": [
|
| 7 |
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{
|
| 8 |
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|
| 9 |
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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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| 16 |
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| 17 |
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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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|
| 35 |
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|
| 36 |
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|
| 37 |
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|
| 38 |
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| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 45 |
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|
| 46 |
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|
| 47 |
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|
| 48 |
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|
| 49 |
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|
| 50 |
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|
| 51 |
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|
| 52 |
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|
| 53 |
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|
| 54 |
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|
| 55 |
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|
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|
| 58 |
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|
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|
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|
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|
| 64 |
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|
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|
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|
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
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|
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|
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|
| 75 |
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|
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|
| 77 |
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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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|
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|
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|
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|
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|
| 98 |
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|
| 99 |
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|
| 100 |
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|
| 101 |
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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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|
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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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|
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| 448 |
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|
| 449 |
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|
| 450 |
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| 451 |
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|
| 452 |
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|
| 453 |
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| 454 |
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| 455 |
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| 456 |
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}
|
results/minishlab__potion-base-4M/81b1802ada41afcd0987a37dc15e569c9fa76f04/MSMARCO.json
ADDED
|
@@ -0,0 +1,456 @@
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|
| 1 |
+
{
|
| 2 |
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"dataset_revision": "c5a29a104738b98a9e76336939199e264163d4a0",
|
| 3 |
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"task_name": "MSMARCO",
|
| 4 |
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"mteb_version": "1.18.0",
|
| 5 |
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"scores": {
|
| 6 |
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"train": [
|
| 7 |
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{
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| 8 |
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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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| 28 |
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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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| 35 |
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|
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|
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| 449 |
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| 450 |
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| 451 |
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|
| 452 |
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| 453 |
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| 454 |
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| 456 |
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|
results/minishlab__potion-base-8M/dcbec7aa2d52fc76754ac6291803feedd8c619ce/MSMARCO.json
ADDED
|
@@ -0,0 +1,456 @@
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|
| 1 |
+
{
|
| 2 |
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"dataset_revision": "c5a29a104738b98a9e76336939199e264163d4a0",
|
| 3 |
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"task_name": "MSMARCO",
|
| 4 |
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|
| 5 |
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"scores": {
|
| 6 |
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"train": [
|
| 7 |
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{
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| 8 |
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|
| 9 |
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| 10 |
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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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| 27 |
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| 28 |
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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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|
| 35 |
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| 39 |
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|
| 40 |
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|
| 41 |
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| 448 |
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| 449 |
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| 450 |
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| 451 |
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| 452 |
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| 453 |
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| 454 |
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| 456 |
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|
results/nomic-ai__nomic-embed-text-v1-ablated/7d948905c5d5d3874fa55a925d68e49dbf411e5f/model_meta.json
CHANGED
|
@@ -1 +1 @@
|
|
| 1 |
-
{"name": "nomic-ai/nomic-embed-text-v1-ablated", "revision": "7d948905c5d5d3874fa55a925d68e49dbf411e5f", "release_date": "2024-01-15", "languages": ["eng-Latn"], "n_parameters": null, "max_tokens": 8192.0, "embed_dim": 768, "license": "apache-2.0", "open_weights": true, "public_training_code": null, "framework": ["Sentence Transformers", "PyTorch"], "reference": "https://huggingface.co/nomic-ai/nomic-embed-text-v1-ablated", "similarity_fn_name": "cosine", "use_instructions": true, "training_datasets": null, "adapted_from": null, "superseded_by": null, "loader": "NomicWrapper"}
|
|
|
|
| 1 |
+
{"name": "nomic-ai/nomic-embed-text-v1-ablated", "revision": "7d948905c5d5d3874fa55a925d68e49dbf411e5f", "release_date": "2024-01-15", "languages": ["eng-Latn"], "n_parameters": null, "max_tokens": 8192.0, "embed_dim": 768, "license": "apache-2.0", "open_weights": true, "public_training_code": null, "framework": ["Sentence Transformers", "PyTorch"], "reference": "https://huggingface.co/nomic-ai/nomic-embed-text-v1-ablated", "similarity_fn_name": "cosine", "use_instructions": true, "training_datasets": null, "adapted_from": null, "superseded_by": null, "loader": "NomicWrapper"}
|