Training in progress, step 3000

Information-Retrieval_evaluation_BeIR-touche2020-subset-test_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoArguAna_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoClimateFEVER_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoDBPedia_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoFEVER_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoFiQA2018_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoHotpotQA_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoMSMARCO_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoNFCorpus_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoNQ_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoQuoraRetrieval_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoSCIDOCS_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoSciFact_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoTouche2020_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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NanoBEIR_evaluation_mean_results.csv

@@ -7,3 +7,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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config.json

@@ -1,45 +1,24 @@
 {
   "architectures": [
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+    "BertModel"
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-  "norm_eps": 1e-05,
+  "intermediate_size": 1536,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
   "num_attention_heads": 12,
-  "num_hidden_layers": 22,
-  "pad_token_id": 50283,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
   "position_embedding_type": "absolute",
-  "repad_logits_with_grad": false,
-  "sep_token_id": 50282,
-  "sparse_pred_ignore_index": -100,
-  "sparse_prediction": false,
   "transformers_version": "4.57.3",
-  "vocab_size": 50368
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
 }

eval/Information-Retrieval_evaluation_NanoMSMARCO_results.csv

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eval/Information-Retrieval_evaluation_NanoNQ_results.csv

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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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