Training in progress, epoch 1

config.json

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+{
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0"
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+  "intermediate_size": 3072,
+  "label2id": {
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+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

eval/Information-Retrieval_evaluation_dim_128_results.csv

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eval/Information-Retrieval_evaluation_dim_256_results.csv

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+epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
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eval/Information-Retrieval_evaluation_dim_512_results.csv

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+epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
+1.0,2,0.4019607843137255,0.5490196078431373,0.6862745098039216,0.7745098039215687,0.4019607843137255,0.4019607843137255,0.18300653594771235,0.5490196078431373,0.13725490196078427,0.6862745098039216,0.07745098039215684,0.7745098039215687,0.512180983504513,0.5747623594698829,0.5205335935305102

eval/Information-Retrieval_evaluation_dim_64_results.csv

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+epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
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eval/Information-Retrieval_evaluation_dim_768_results.csv

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+epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
+1.0,2,0.4019607843137255,0.5784313725490197,0.7058823529411765,0.7843137254901961,0.4019607843137255,0.4019607843137255,0.19281045751633982,0.5784313725490197,0.14117647058823524,0.7058823529411765,0.07843137254901959,0.7843137254901961,0.5180944600062248,0.5817103636294029,0.5254064096528579
+2.0,4,0.4019607843137255,0.5686274509803921,0.7156862745098039,0.7843137254901961,0.4019607843137255,0.4019607843137255,0.18954248366013068,0.5686274509803921,0.14313725490196072,0.7156862745098039,0.07843137254901959,0.7843137254901961,0.5188958916900095,0.5825071579190789,0.5270476353988504

model.safetensors

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runs/May01_03-32-52_modal/events.out.tfevents.1746070374.modal.2.0

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special_tokens_map.json

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+{
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+    "lstrip": false,
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+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
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+      "content": "[PAD]",
+      "lstrip": false,
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+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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