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-mae
+  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-mae
+
+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: 0.2200
+- Mse: 0.0781
+- Mae: 0.2200
+- Pearson Corr: 0.3461
+- Spearman Corr: 0.3129
+- Cosine Sim: 0.9050
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------------:|:-------------:|:----------:|
+| 0.2886        | 1.0   | 41   | 0.2213          | 0.0742 | 0.2213 | 0.0650       | 0.0604        | 0.9037     |
+| 0.2582        | 2.0   | 82   | 0.2223          | 0.0714 | 0.2223 | 0.1319       | 0.1417        | 0.9052     |
+| 0.2615        | 3.0   | 123  | 0.2094          | 0.0670 | 0.2094 | 0.2859       | 0.2753        | 0.9113     |
+| 0.2247        | 4.0   | 164  | 0.2152          | 0.0733 | 0.2152 | 0.3126       | 0.2705        | 0.9075     |
+| 0.1942        | 5.0   | 205  | 0.2363          | 0.0890 | 0.2363 | 0.3631       | 0.3424        | 0.9112     |
+| 0.1758        | 6.0   | 246  | 0.2193          | 0.0776 | 0.2193 | 0.3528       | 0.3247        | 0.9106     |
+| 0.166         | 7.0   | 287  | 0.2200          | 0.0781 | 0.2200 | 0.3461       | 0.3129        | 0.9050     |
+
+
+### 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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