Training in progress, step 3000

Information-Retrieval_evaluation_BeIR-touche2020-subset-test_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoArguAna_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoClimateFEVER_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoDBPedia_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoFEVER_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoFiQA2018_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoHotpotQA_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoMSMARCO_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoNFCorpus_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.32,0.46,0.54,0.6,0.32,0.012390714058566699,0.28,0.03091743967375776,0.26,0.0669147297391448,0.222,0.09088305778625912,0.4105238095238095,0.2483348722648785,0.09280425392585814
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Information-Retrieval_evaluation_NanoNQ_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.18,0.34,0.4,0.48,0.18,0.16,0.11333333333333333,0.32,0.08,0.37,0.04800000000000001,0.45,0.27455555555555555,0.30483462455030724,0.26647869540792385
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Information-Retrieval_evaluation_NanoQuoraRetrieval_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.96,0.98,1.0,1.0,0.96,0.8373333333333332,0.4133333333333333,0.9520000000000001,0.25999999999999995,0.9793333333333334,0.13999999999999999,1.0,0.975,0.9755732089084438,0.9623253968253969
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Information-Retrieval_evaluation_NanoSCIDOCS_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoSciFact_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.22,0.3,0.32,0.38,0.22,0.195,0.12,0.285,0.07600000000000001,0.305,0.044000000000000004,0.365,0.2718333333333333,0.28918208458247957,0.27817432559902106
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Information-Retrieval_evaluation_NanoTouche2020_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.46938775510204084,0.6530612244897959,0.8163265306122449,0.9591836734693877,0.46938775510204084,0.03304169886606065,0.4081632653061224,0.08663742657609082,0.3877551020408163,0.13074375193904886,0.34285714285714286,0.2206088169640079,0.6090055069646906,0.38115064093925494,0.2635297595122428
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NanoBEIR_evaluation_mean_results.csv

@@ -4,3 +4,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.35149136577708007,0.4902354788069073,0.5658712715855574,0.6491679748822605,0.35149136577708007,0.18446485464636025,0.2257561486132915,0.28725844278832385,0.18121193092621668,0.34314132490039767,0.1285274725274725,0.41258506430111763,0.44353216964441444,0.37688675285510337,0.3106340488088058
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config.json

@@ -5,6 +5,7 @@
   "attention_probs_dropout_prob": 0.1,
   "classifier_dropout": null,
   "dtype": "float32",
+  "gradient_checkpointing": false,
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.1,
   "hidden_size": 384,
@@ -14,7 +15,7 @@
   "max_position_embeddings": 512,
   "model_type": "bert",
   "num_attention_heads": 12,
-  "num_hidden_layers": 12,
+  "num_hidden_layers": 6,
   "pad_token_id": 0,
   "position_embedding_type": "absolute",
   "transformers_version": "4.57.3",

eval/Information-Retrieval_evaluation_NanoMSMARCO_results.csv

@@ -85,3 +85,16 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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eval/NanoBEIR_evaluation_mean_results.csv

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final_metrics.json

@@ -1,231 +1,231 @@
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+    "BeIR-touche2020-subset-test_cosine_precision@3": 0.8095238095238094,
+    "BeIR-touche2020-subset-test_cosine_precision@5": 0.7510204081632652,
+    "BeIR-touche2020-subset-test_cosine_precision@10": 0.6448979591836734,
+    "BeIR-touche2020-subset-test_cosine_recall@1": 0.01945012749314946,
+    "BeIR-touche2020-subset-test_cosine_recall@3": 0.0537432819678873,
+    "BeIR-touche2020-subset-test_cosine_recall@5": 0.08295390754493644,
+    "BeIR-touche2020-subset-test_cosine_recall@10": 0.14269962051162913,
+    "BeIR-touche2020-subset-test_cosine_ndcg@10": 0.698044370091445,
+    "BeIR-touche2020-subset-test_cosine_mrr@10": 0.9387755102040817,
+    "BeIR-touche2020-subset-test_cosine_map@100": 0.29990375282881515
   }
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bce462da976c7206ad29bb0359416a99e061f3524da838abfdd2b633ebde15fe
-size 133462128
+oid sha256:e4cba7736f0b233c21227eb51b3b05d427e51440fd611d6327986fbae3b85479
+size 90864192

tokenizer_config.json

@@ -41,14 +41,14 @@
       "special": true
     }
   },
-  "clean_up_tokenization_spaces": true,
+  "clean_up_tokenization_spaces": false,
   "cls_token": "[CLS]",
   "do_basic_tokenize": true,
   "do_lower_case": true,
   "extra_special_tokens": {},
   "mask_token": "[MASK]",
   "max_length": 128,
-  "model_max_length": 512,
+  "model_max_length": 256,
   "never_split": null,
   "pad_to_multiple_of": null,
   "pad_token": "[PAD]",