Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+model-index:
+- name: jun
+  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. -->
+
+# jun
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3547
+- Topology Accuracy: 0.9844
+- Service Accuracy: 0.9707
+- Combined Accuracy: 0.9775
+
+## 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: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 50
+- num_epochs: 15
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Topology Accuracy | Service Accuracy | Combined Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:----------------:|:-----------------:|
+| 0.6873        | 1.0   | 96   | 0.6360          | 0.9199            | 0.7207           | 0.8203            |
+| 0.5304        | 2.0   | 192  | 0.4932          | 0.9648            | 0.8320           | 0.8984            |
+| 0.3932        | 3.0   | 288  | 0.4083          | 0.9746            | 0.9102           | 0.9424            |
+| 0.3548        | 4.0   | 384  | 0.3664          | 0.9766            | 0.9551           | 0.9658            |
+| 0.3072        | 5.0   | 480  | 0.3418          | 0.9824            | 0.9727           | 0.9775            |
+| 0.3076        | 6.0   | 576  | 0.3551          | 0.9824            | 0.9688           | 0.9756            |
+| 0.3191        | 7.0   | 672  | 0.3611          | 0.9805            | 0.9668           | 0.9736            |
+| 0.3035        | 8.0   | 768  | 0.3617          | 0.9824            | 0.9648           | 0.9736            |
+| 0.3026        | 9.0   | 864  | 0.3569          | 0.9844            | 0.9648           | 0.9746            |
+| 0.3027        | 10.0  | 960  | 0.3557          | 0.9844            | 0.9629           | 0.9736            |
+| 0.3021        | 11.0  | 1056 | 0.3584          | 0.9824            | 0.9668           | 0.9746            |
+| 0.3005        | 12.0  | 1152 | 0.3562          | 0.9844            | 0.9688           | 0.9766            |
+| 0.3179        | 13.0  | 1248 | 0.3547          | 0.9844            | 0.9688           | 0.9766            |
+| 0.3011        | 14.0  | 1344 | 0.3552          | 0.9844            | 0.9707           | 0.9775            |
+| 0.3018        | 15.0  | 1440 | 0.3547          | 0.9844            | 0.9707           | 0.9775            |
+
+
+### Framework versions
+
+- Transformers 4.56.1
+- Pytorch 2.8.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.0

config.json

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+{
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForMultiHeadClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "dtype": "float32",
+  "hidden_dim": 3072,
+  "initializer_range": 0.02,
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "transformers_version": "4.56.1",
+  "vocab_size": 30522
+}

model.safetensors

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+size 267833336

training_args.bin

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