End of training

README.md

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+---
+library_name: transformers
+base_model: huawei-noah/TinyBERT_General_4L_312D
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: NF4-KD-NID
+  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. -->
+
+# NF4-KD-NID
+
+This model is a fine-tuned version of [huawei-noah/TinyBERT_General_4L_312D](https://huggingface.co/huawei-noah/TinyBERT_General_4L_312D) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0419
+- Accuracy: 0.9919
+- Precision: 0.9744
+- Recall: 0.9469
+- F1 score: 0.9546
+
+## 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: 650
+- eval_batch_size: 650
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 15
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1 score |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:|
+| 0.2112        | 1.0   | 1828  | 0.1824          | 0.9775   | 0.7759    | 0.7784 | 0.7742   |
+| 0.1196        | 2.0   | 3656  | 0.1061          | 0.9850   | 0.9060    | 0.8522 | 0.8502   |
+| 0.0956        | 3.0   | 5484  | 0.0855          | 0.9874   | 0.9140    | 0.8833 | 0.8858   |
+| 0.0823        | 4.0   | 7312  | 0.0708          | 0.9891   | 0.9204    | 0.8982 | 0.9029   |
+| 0.0653        | 5.0   | 9140  | 0.0628          | 0.9897   | 0.9313    | 0.8985 | 0.9070   |
+| 0.066         | 6.0   | 10968 | 0.0572          | 0.9901   | 0.9206    | 0.9132 | 0.9106   |
+| 0.0546        | 7.0   | 12796 | 0.0534          | 0.9907   | 0.9284    | 0.9156 | 0.9187   |
+| 0.0486        | 8.0   | 14624 | 0.0511          | 0.9909   | 0.9287    | 0.9184 | 0.9199   |
+| 0.0473        | 9.0   | 16452 | 0.0490          | 0.9911   | 0.9732    | 0.9284 | 0.9346   |
+| 0.0483        | 10.0  | 18280 | 0.0469          | 0.9914   | 0.9788    | 0.9237 | 0.9344   |
+| 0.0435        | 11.0  | 20108 | 0.0451          | 0.9915   | 0.9722    | 0.9323 | 0.9360   |
+| 0.0388        | 12.0  | 21936 | 0.0429          | 0.9917   | 0.9757    | 0.9395 | 0.9477   |
+| 0.039         | 13.0  | 23764 | 0.0426          | 0.9917   | 0.9758    | 0.9514 | 0.9597   |
+| 0.0362        | 14.0  | 25592 | 0.0423          | 0.9918   | 0.9743    | 0.9467 | 0.9542   |
+| 0.0357        | 15.0  | 27420 | 0.0419          | 0.9919   | 0.9744    | 0.9469 | 0.9546   |
+
+
+### Framework versions
+
+- Transformers 4.49.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.4.1
+- Tokenizers 0.21.1

config.json

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+{
+  "_name_or_path": "huawei-noah/TinyBERT_General_4L_312D",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "attention_probs_dropout_prob": 0.1,
+  "cell": {},
+  "dim": 312,
+  "dropout": 0.1,
+  "emb_size": 312,
+  "hidden_act": "gelu",
+  "hidden_dim": 3072,
+  "hidden_dropout_prob": 0.1,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6",
+    "7": "LABEL_7",
+    "8": "LABEL_8",
+    "9": "LABEL_9",
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+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 4,
+  "pad_token_id": 0,
+  "pre_trained": "",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "structure": [],
+  "torch_dtype": "float32",
+  "transformers_version": "4.49.0",
+  "type_vocab_size": 2,
+  "vocab_size": 30522
+}

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