Duplicate from tangminhanh/results

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README.md

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+---
+license: mit
+base_model: tangminhanh/results
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: results
+  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. -->
+
+# results
+
+This model is a fine-tuned version of [tangminhanh/results](https://huggingface.co/tangminhanh/results) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0214
+- Accuracy: 0.8673
+- F1: 0.8828
+- Precision: 0.8907
+- Recall: 0.8750
+
+## 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
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.0959        | 1.0   | 816  | 0.0287          | 0.7330   | 0.7966 | 0.8666    | 0.7371 |
+| 0.0223        | 2.0   | 1632 | 0.0203          | 0.8256   | 0.8587 | 0.8922    | 0.8277 |
+| 0.0171        | 3.0   | 2448 | 0.0197          | 0.8348   | 0.8639 | 0.8824    | 0.8463 |
+| 0.0116        | 4.0   | 3264 | 0.0194          | 0.8486   | 0.8708 | 0.8873    | 0.8548 |
+| 0.0101        | 5.0   | 4080 | 0.0198          | 0.8532   | 0.8704 | 0.8798    | 0.8612 |
+| 0.008         | 6.0   | 4896 | 0.0200          | 0.8550   | 0.8742 | 0.8872    | 0.8615 |
+| 0.0065        | 7.0   | 5712 | 0.0204          | 0.8614   | 0.8775 | 0.8867    | 0.8686 |
+| 0.0056        | 8.0   | 6528 | 0.0208          | 0.8587   | 0.8768 | 0.8858    | 0.8679 |
+| 0.0048        | 9.0   | 7344 | 0.0214          | 0.8624   | 0.8781 | 0.8875    | 0.8689 |
+| 0.0044        | 10.0  | 8160 | 0.0214          | 0.8673   | 0.8828 | 0.8907    | 0.8750 |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

added_tokens.json

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config.json

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+  "_name_or_path": "tangminhanh/results",
+  "architectures": [
+    "DebertaV2ForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Biometric",
+    "1": "Document",
+    "2": "Asset Management",
+    "3": "Data Security Incident",
+    "4": "Off Boarding",
+    "5": "CCTV",
+    "6": "Network",
+    "7": "Network and Infrastructure Design",
+    "8": "Circuit",
+    "9": "Outage",
+    "10": "Network Security",
+    "11": "Notification",
+    "12": "System Security",
+    "13": "Server Management",
+    "14": "Server Projects",
+    "15": "Services Management",
+    "16": "User Account",
+    "17": "Checklist",
+    "18": "Deployment / Movement",
+    "19": "CASA",
+    "20": "Email",
+    "21": "General Assistance",
+    "22": "Hardware",
+    "23": "Printer",
+    "24": "Software",
+    "25": "Telephony",
+    "26": "TV Advertisement",
+    "27": "Development",
+    "28": "New Hire Shadowing",
+    "29": "Web/Application Security",
+    "30": "On Boarding",
+    "31": "BCP Activation",
+    "32": "Ticketing Support",
+    "33": "Email Security",
+    "34": "TPMO",
+    "35": "Food Allowance",
+    "36": "Procurement",
+    "37": "Compliance",
+    "38": "P&C Payroll",
+    "39": "Unnamed: 33",
+    "40": "P&C Allowance",
+    "41": "Server",
+    "42": "P&C HR Documents",
+    "43": "HRDT - HRIS"
+  },
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+    "CASA": 19,
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+    "Checklist": 17,
+    "Circuit": 8,
+    "Compliance": 37,
+    "Data Security Incident": 3,
+    "Deployment / Movement": 18,
+    "Development": 27,
+    "Document": 1,
+    "Email": 20,
+    "Email Security": 33,
+    "Food Allowance": 35,
+    "General Assistance": 21,
+    "HRDT - HRIS": 43,
+    "Hardware": 22,
+    "Network": 6,
+    "Network Security": 10,
+    "Network and Infrastructure Design": 7,
+    "New Hire Shadowing": 28,
+    "Notification": 11,
+    "Off Boarding": 4,
+    "On Boarding": 30,
+    "Outage": 9,
+    "P&C Allowance": 40,
+    "P&C HR Documents": 42,
+    "P&C Payroll": 38,
+    "Printer": 23,
+    "Procurement": 36,
+    "Server": 41,
+    "Server Management": 13,
+    "Server Projects": 14,
+    "Services Management": 15,
+    "Software": 24,
+    "System Security": 12,
+    "TPMO": 34,
+    "TV Advertisement": 26,
+    "Telephony": 25,
+    "Ticketing Support": 32,
+    "Unnamed: 33": 39,
+    "User Account": 16,
+    "Web/Application Security": 29
+  },
+  "layer_norm_eps": 1e-07,
+  "max_position_embeddings": 512,
+  "max_relative_positions": -1,
+  "model_type": "deberta-v2",
+  "norm_rel_ebd": "layer_norm",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
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+  "pooler_dropout": 0,
+  "pooler_hidden_act": "gelu",
+  "pooler_hidden_size": 768,
+  "pos_att_type": [
+    "p2c",
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+  "position_biased_input": false,
+  "position_buckets": 256,
+  "problem_type": "multi_label_classification",
+  "relative_attention": true,
+  "share_att_key": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.2",
+  "type_vocab_size": 0,
+  "vocab_size": 128100
+}

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