End of training

README.md

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+---
+license: cc-by-nc-4.0
+base_model: NYTK/PULI-BERT-Large
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: kmdb_ner_model
+  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. -->
+
+# kmdb_ner_model
+
+This model is a fine-tuned version of [NYTK/PULI-BERT-Large](https://huggingface.co/NYTK/PULI-BERT-Large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0405
+- Precision: 0.8023
+- Recall: 0.8261
+- F1: 0.8140
+- Accuracy: 0.9842
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0613        | 0.11  | 1000  | 0.0575          | 0.7102    | 0.7359 | 0.7228 | 0.9776   |
+| 0.0559        | 0.23  | 2000  | 0.0525          | 0.7108    | 0.7611 | 0.7351 | 0.9788   |
+| 0.0569        | 0.34  | 3000  | 0.0512          | 0.7375    | 0.7856 | 0.7608 | 0.9798   |
+| 0.0481        | 0.45  | 4000  | 0.0496          | 0.7402    | 0.7975 | 0.7678 | 0.9803   |
+| 0.041         | 0.57  | 5000  | 0.0474          | 0.7567    | 0.7981 | 0.7769 | 0.9809   |
+| 0.0434        | 0.68  | 6000  | 0.0463          | 0.7588    | 0.7853 | 0.7718 | 0.9813   |
+| 0.0577        | 0.8   | 7000  | 0.0462          | 0.7592    | 0.7896 | 0.7741 | 0.9812   |
+| 0.0422        | 0.91  | 8000  | 0.0428          | 0.7820    | 0.8057 | 0.7937 | 0.9828   |
+| 0.0346        | 1.02  | 9000  | 0.0443          | 0.7758    | 0.8153 | 0.7951 | 0.9825   |
+| 0.0301        | 1.14  | 10000 | 0.0431          | 0.7831    | 0.8124 | 0.7974 | 0.9830   |
+| 0.0305        | 1.25  | 11000 | 0.0427          | 0.7955    | 0.8162 | 0.8057 | 0.9834   |
+| 0.0347        | 1.36  | 12000 | 0.0420          | 0.7923    | 0.8171 | 0.8045 | 0.9834   |
+| 0.0397        | 1.48  | 13000 | 0.0422          | 0.7923    | 0.8220 | 0.8069 | 0.9835   |
+| 0.0267        | 1.59  | 14000 | 0.0411          | 0.7970    | 0.8209 | 0.8087 | 0.9838   |
+| 0.03          | 1.71  | 15000 | 0.0415          | 0.7946    | 0.8230 | 0.8085 | 0.9838   |
+| 0.0311        | 1.82  | 16000 | 0.0407          | 0.8023    | 0.8253 | 0.8136 | 0.9842   |
+| 0.0283        | 1.93  | 17000 | 0.0405          | 0.8023    | 0.8261 | 0.8140 | 0.9842   |
+
+
+### Framework versions
+
+- Transformers 4.38.1
+- Pytorch 2.0.1+cu117
+- Datasets 2.16.1
+- Tokenizers 0.15.0

config.json

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+{
+  "_name_or_path": "NYTK/PULI-BERT-Large",
+  "architectures": [
+    "MegatronBertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "O",
+    "1": "B-NEG-ORG",
+    "2": "B-POS-ORG",
+    "3": "I-NEG-ORG",
+    "4": "I-POS-ORG",
+    "5": "B-NEG-PER",
+    "6": "B-POS-PER",
+    "7": "I-NEG-PER",
+    "8": "I-POS-PER",
+    "9": "B-NEG-LOC",
+    "10": "B-POS-LOC",
+    "11": "I-NEG-LOC",
+    "12": "I-POS-LOC"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "B-NEG-LOC": 9,
+    "B-NEG-ORG": 1,
+    "B-NEG-PER": 5,
+    "B-POS-LOC": 10,
+    "B-POS-ORG": 2,
+    "B-POS-PER": 6,
+    "I-NEG-LOC": 11,
+    "I-NEG-ORG": 3,
+    "I-NEG-PER": 7,
+    "I-POS-LOC": 12,
+    "I-POS-ORG": 4,
+    "I-POS-PER": 8,
+    "O": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "megatron-bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "tokenizer_type": "BertWordPieceCase",
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 32256
+}

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special_tokens_map.json

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tokenizer_config.json

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+}

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