Model save

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- accuracy
+model-index:
+- name: bge_large_cn_new_prompt_llama3_70_2
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# bge_large_cn_new_prompt_llama3_70_2
+
+This model was trained from scratch on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9337
+- Precision: 0.4748
+- Recall: 0.3645
+- F1 Macro: 0.3499
+- Accuracy: 0.4695
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0003
+- train_batch_size: 2048
+- eval_batch_size: 1024
+- seed: 0
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1 Macro | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:|
+| No log        | 0       | 0    | 10.0773         | 0.0731    | 0.1667 | 0.0201   | 0.0638   |
+| 0.9787        | 2.9326  | 1000 | 0.9896          | 0.4564    | 0.3443 | 0.3343   | 0.4531   |
+| 0.9384        | 5.8651  | 2000 | 0.9622          | 0.4761    | 0.3558 | 0.3436   | 0.4648   |
+| 0.9347        | 8.7977  | 3000 | 0.9476          | 0.4705    | 0.3592 | 0.3447   | 0.4594   |
+| 0.9172        | 11.7302 | 4000 | 0.9409          | 0.4716    | 0.3608 | 0.3453   | 0.4613   |
+| 0.9073        | 14.6628 | 5000 | 0.9369          | 0.4661    | 0.3665 | 0.3535   | 0.4648   |
+| 0.8973        | 17.5953 | 6000 | 0.9337          | 0.4748    | 0.3645 | 0.3499   | 0.4695   |
+
+
+### Framework versions
+
+- Transformers 4.43.3
+- Pytorch 2.4.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

final/config.json

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+{
+  "_name_or_path": "/mnt/workspace/models/bge-large-zh-v1.5",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": 0.0,
+  "directionality": "bidi",
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "problem_type": "regression",
+  "torch_dtype": "float32",
+  "transformers_version": "4.43.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 21128
+}

final/model.safetensors

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final/special_tokens_map.json

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+}

final/tokenizer_config.json

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+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "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]"
+}

final/training_args.bin

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model.safetensors

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