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: j
+  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. -->
+
+# j
+
+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: 0.3746
+- Topology Accuracy: 0.9851
+- Service Accuracy: 0.9435
+- Combined Accuracy: 0.9643
+
+## 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: 5e-05
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:----------------:|:-----------------:|
+| 1.016         | 1.0   | 64   | 0.9725          | 0.7411            | 0.6220           | 0.6815            |
+| 0.7234        | 2.0   | 128  | 0.6385          | 0.9643            | 0.6935           | 0.8289            |
+| 0.6038        | 3.0   | 192  | 0.5826          | 0.9345            | 0.7440           | 0.8393            |
+| 0.5014        | 4.0   | 256  | 0.5192          | 0.9583            | 0.7738           | 0.8661            |
+| 0.3959        | 5.0   | 320  | 0.4845          | 0.9732            | 0.7768           | 0.875             |
+| 0.4165        | 6.0   | 384  | 0.4579          | 0.9762            | 0.8601           | 0.9182            |
+| 0.3699        | 7.0   | 448  | 0.4156          | 0.9851            | 0.9286           | 0.9568            |
+| 0.3272        | 8.0   | 512  | 0.3777          | 0.9851            | 0.9524           | 0.9688            |
+| 0.3091        | 9.0   | 576  | 0.3714          | 0.9851            | 0.9464           | 0.9658            |
+| 0.3092        | 10.0  | 640  | 0.3814          | 0.9821            | 0.9464           | 0.9643            |
+| 0.3221        | 11.0  | 704  | 0.3811          | 0.9821            | 0.9405           | 0.9613            |
+| 0.3033        | 12.0  | 768  | 0.3724          | 0.9851            | 0.9405           | 0.9628            |
+| 0.304         | 13.0  | 832  | 0.3741          | 0.9881            | 0.9435           | 0.9658            |
+| 0.3051        | 14.0  | 896  | 0.3743          | 0.9851            | 0.9435           | 0.9643            |
+| 0.3039        | 15.0  | 960  | 0.3746          | 0.9851            | 0.9435           | 0.9643            |
+
+
+### 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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