Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+model-index:
+- name: bert-reg-crossencoder-mse
+  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. -->
+
+# bert-reg-crossencoder-mse
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0752
+- Mse: 0.0752
+- Mae: 0.2120
+- Pearson Corr: 0.3937
+- Spearman Corr: 0.3178
+- Cosine Sim: 0.9163
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 7
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Mse    | Mae    | Pearson Corr | Spearman Corr | Cosine Sim |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------------:|:-------------:|:----------:|
+| 0.1034        | 1.0   | 41   | 0.0704          | 0.0704 | 0.2198 | 0.1914       | 0.2429        | 0.9070     |
+| 0.097         | 2.0   | 82   | 0.0739          | 0.0739 | 0.2161 | 0.2185       | 0.2208        | 0.9059     |
+| 0.0877        | 3.0   | 123  | 0.0663          | 0.0663 | 0.2154 | 0.3214       | 0.2426        | 0.9133     |
+| 0.0679        | 4.0   | 164  | 0.0723          | 0.0723 | 0.2054 | 0.3722       | 0.3382        | 0.9175     |
+| 0.0569        | 5.0   | 205  | 0.0644          | 0.0644 | 0.2058 | 0.3867       | 0.3552        | 0.9155     |
+| 0.0408        | 6.0   | 246  | 0.0773          | 0.0773 | 0.2102 | 0.4045       | 0.3105        | 0.9190     |
+| 0.0317        | 7.0   | 287  | 0.0752          | 0.0752 | 0.2120 | 0.3937       | 0.3178        | 0.9163     |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.5.0+cu121
+- Datasets 3.1.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "bert-base-uncased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "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"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "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": "4.44.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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