Training in progress, step 3000

Information-Retrieval_evaluation_BeIR-touche2020-subset-test_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoArguAna_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoClimateFEVER_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoDBPedia_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoFEVER_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoFiQA2018_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoHotpotQA_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoMSMARCO_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.34,0.58,0.7,0.76,0.34,0.34,0.19333333333333333,0.58,0.14,0.7,0.07600000000000001,0.76,0.47455555555555556,0.5436893725288487,0.4851846595537516
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Information-Retrieval_evaluation_NanoNFCorpus_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.36,0.48,0.6,0.72,0.36,0.0129285725459343,0.32666666666666666,0.052512655860219616,0.308,0.0796960890745353,0.272,0.11712381596009674,0.4538809523809524,0.3005415031427539,0.11622108461238956
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Information-Retrieval_evaluation_NanoNQ_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoQuoraRetrieval_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.86,0.96,0.96,1.0,0.86,0.7473333333333332,0.4,0.9253333333333333,0.25599999999999995,0.946,0.13999999999999999,1.0,0.9166666666666667,0.9334595728726137,0.9060476190476191
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Information-Retrieval_evaluation_NanoSCIDOCS_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.42,0.72,0.78,0.84,0.42,0.08866666666666667,0.38,0.23566666666666664,0.30800000000000005,0.3176666666666667,0.20199999999999999,0.4136666666666667,0.5726904761904762,0.3971521362424026,0.3218908255251066
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Information-Retrieval_evaluation_NanoSciFact_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.4,0.6,0.66,0.8,0.4,0.365,0.22666666666666668,0.585,0.152,0.65,0.08999999999999998,0.79,0.5277936507936508,0.5889710099074495,0.5300978155031729
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Information-Retrieval_evaluation_NanoTouche2020_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.5918367346938775,0.8775510204081632,0.9183673469387755,0.9795918367346939,0.5918367346938775,0.043240954475539835,0.5714285714285714,0.12058213731748707,0.5061224489795918,0.17533208842326845,0.40204081632653066,0.27009385945305586,0.7319403952057012,0.46620386185733503,0.35203423103073495
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NanoBEIR_evaluation_mean_results.csv

@@ -9,3 +9,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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config.json

@@ -15,7 +15,7 @@
   "max_position_embeddings": 512,
   "model_type": "bert",
   "num_attention_heads": 12,
-  "num_hidden_layers": 6,
+  "num_hidden_layers": 12,
   "pad_token_id": 0,
   "position_embedding_type": "absolute",
   "transformers_version": "4.57.3",

eval/Information-Retrieval_evaluation_NanoMSMARCO_results.csv

@@ -150,3 +150,16 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 2.873563218390805,2500,0.32,0.54,0.62,0.74,0.32,0.32,0.18,0.54,0.124,0.62,0.07400000000000001,0.74,0.4494682539682539,0.5186670992126912,0.46088793505922276
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eval/NanoBEIR_evaluation_mean_results.csv

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final_metrics.json

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@@ -48,7 +48,7 @@
   "extra_special_tokens": {},
   "mask_token": "[MASK]",
   "max_length": 128,
-  "model_max_length": 256,
+  "model_max_length": 128,
   "never_split": null,
   "pad_to_multiple_of": null,
   "pad_token": "[PAD]",