Training in progress, step 3375

Information-Retrieval_evaluation_BeIR-touche2020-subset-test_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoArguAna_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoClimateFEVER_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoDBPedia_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoFEVER_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoFiQA2018_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoHotpotQA_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoMSMARCO_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoNFCorpus_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoNQ_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoQuoraRetrieval_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoSCIDOCS_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoSciFact_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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Information-Retrieval_evaluation_NanoTouche2020_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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NanoBEIR_evaluation_mean_results.csv

@@ -23,3 +23,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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config.json

@@ -1,45 +1,24 @@
 {
   "architectures": [
-    "ModernBertModel"
+    "BertModel"
   ],
-  "attention_bias": false,
-  "attention_dropout": 0.0,
-  "bos_token_id": 50281,
-  "classifier_activation": "gelu",
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-  "classifier_pooling": "mean",
-  "cls_token_id": 50281,
-  "decoder_bias": true,
-  "deterministic_flash_attn": false,
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
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-  "gradient_checkpointing": false,
-  "hidden_activation": "gelu",
-  "hidden_size": 768,
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+  "intermediate_size": 1536,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
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   "num_attention_heads": 12,
-  "num_hidden_layers": 22,
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+  "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,
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   "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

@@ -266,3 +266,17 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
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final_metrics.json

@@ -1,231 +1,231 @@
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