end of training

README.md

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+---
+license: apache-2.0
+base_model: shibing624/text2vec-base-chinese
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: cosent-similarity-text2vec
+  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. -->
+
+# cosent-similarity-text2vec
+
+This model is a fine-tuned version of [shibing624/text2vec-base-chinese](https://huggingface.co/shibing624/text2vec-base-chinese) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1356
+- Accuracy: 0.9737
+- F1: 0.9783
+- Precision: 0.9783
+- Recall: 0.9783
+
+## 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: 2e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| No log        | 1.0   | 22   | 0.3018          | 0.8816   | 0.8941 | 0.9744    | 0.8261 |
+| No log        | 2.0   | 44   | 0.2175          | 0.9342   | 0.9438 | 0.9767    | 0.9130 |
+| No log        | 3.0   | 66   | 0.1449          | 0.9605   | 0.9670 | 0.9778    | 0.9565 |
+| No log        | 4.0   | 88   | 0.1480          | 0.9605   | 0.9670 | 0.9778    | 0.9565 |
+| No log        | 5.0   | 110  | 0.1356          | 0.9737   | 0.9783 | 0.9783    | 0.9783 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.1

config.json

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+{
+  "_name_or_path": "shibing624/text2vec-base-chinese",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "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": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 21128
+}

model.safetensors

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runs/May10_18-49-48_ml/events.out.tfevents.1715338194.ml.2583346.1

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training_args.bin

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