Training complete

README.md

@@ -1,85 +1,75 @@
----
-license: apache-2.0
-base_model: bert-base-cased
-tags:
-- generated_from_trainer
-metrics:
-- precision
-- recall
-- f1
-- accuracy
-model-index:
-- name: bert-finetuned-ner
-  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. -->
-
-# bert-finetuned-ner
-
-This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.5707
-- Precision: 0.8258
-- Recall: 0.8753
-- F1: 0.8498
-- Accuracy: 0.9254
-
-## 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: 1e-05
-- train_batch_size: 8
-- eval_batch_size: 8
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 20
-
-### Training results
-
-| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.1966        | 1.0   | 680   | 0.3961          | 0.7705    | 0.8096 | 0.7896 | 0.8971   |
-| 0.1487        | 2.0   | 1360  | 0.4435          | 0.7607    | 0.8258 | 0.7919 | 0.8950   |
-| 0.1258        | 3.0   | 2040  | 0.4180          | 0.7727    | 0.8450 | 0.8072 | 0.9052   |
-| 0.1163        | 4.0   | 2720  | 0.4227          | 0.7890    | 0.8418 | 0.8145 | 0.9078   |
-| 0.1019        | 5.0   | 3400  | 0.4721          | 0.7664    | 0.8630 | 0.8118 | 0.9068   |
-| 0.0763        | 6.0   | 4080  | 0.4444          | 0.8033    | 0.8542 | 0.8280 | 0.9172   |
-| 0.0641        | 7.0   | 4760  | 0.4551          | 0.8189    | 0.8550 | 0.8366 | 0.9179   |
-| 0.0615        | 8.0   | 5440  | 0.4615          | 0.8167    | 0.8640 | 0.8397 | 0.9202   |
-| 0.0468        | 9.0   | 6120  | 0.4922          | 0.8104    | 0.8668 | 0.8376 | 0.9205   |
-| 0.0381        | 10.0  | 6800  | 0.4991          | 0.8213    | 0.8642 | 0.8422 | 0.9210   |
-| 0.0381        | 11.0  | 7480  | 0.4950          | 0.8298    | 0.8593 | 0.8443 | 0.9230   |
-| 0.0289        | 12.0  | 8160  | 0.5273          | 0.8220    | 0.8717 | 0.8461 | 0.9232   |
-| 0.026         | 13.0  | 8840  | 0.5366          | 0.8207    | 0.8700 | 0.8446 | 0.9230   |
-| 0.0227        | 14.0  | 9520  | 0.5466          | 0.8240    | 0.8698 | 0.8463 | 0.9230   |
-| 0.02          | 15.0  | 10200 | 0.5530          | 0.8250    | 0.8710 | 0.8474 | 0.9247   |
-| 0.0173        | 16.0  | 10880 | 0.5571          | 0.8235    | 0.8726 | 0.8473 | 0.9244   |
-| 0.0152        | 17.0  | 11560 | 0.5551          | 0.8282    | 0.8700 | 0.8486 | 0.9248   |
-| 0.0146        | 18.0  | 12240 | 0.5686          | 0.8270    | 0.8727 | 0.8492 | 0.9246   |
-| 0.0142        | 19.0  | 12920 | 0.5687          | 0.8258    | 0.8753 | 0.8498 | 0.9259   |
-| 0.0135        | 20.0  | 13600 | 0.5707          | 0.8258    | 0.8753 | 0.8498 | 0.9254   |
-
-
-### Framework versions
-
-- Transformers 4.42.4
-- Pytorch 2.3.1+cu121
-- Datasets 2.20.0
-- Tokenizers 0.19.1
+---
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-ner
+  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. -->
+
+# bert-finetuned-ner
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3391
+- Precision: 0.8826
+- Recall: 0.9138
+- F1: 0.8979
+- Accuracy: 0.9518
+
+## 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: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- 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 | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0318        | 1.0   | 680  | 0.4800          | 0.8075    | 0.8632 | 0.8344 | 0.9183   |
+| 0.0206        | 2.0   | 1360 | 0.4822          | 0.8332    | 0.8634 | 0.8480 | 0.9233   |
+| 0.0116        | 3.0   | 2040 | 0.5227          | 0.8167    | 0.8683 | 0.8417 | 0.9211   |
+| 0.0093        | 4.0   | 2720 | 0.5366          | 0.8230    | 0.8749 | 0.8482 | 0.9246   |
+| 0.0077        | 5.0   | 3400 | 0.5384          | 0.8370    | 0.8688 | 0.8526 | 0.9249   |
+| 0.0061        | 6.0   | 4080 | 0.5450          | 0.8418    | 0.8754 | 0.8583 | 0.9275   |
+| 0.0048        | 7.0   | 4760 | 0.5570          | 0.8346    | 0.8765 | 0.8550 | 0.9262   |
+| 0.0084        | 8.0   | 5440 | 0.5565          | 0.8353    | 0.8765 | 0.8554 | 0.9261   |
+| 0.0073        | 9.0   | 6120 | 0.5693          | 0.8353    | 0.8751 | 0.8547 | 0.9261   |
+| 0.0058        | 10.0  | 6800 | 0.5688          | 0.8361    | 0.8766 | 0.8559 | 0.9265   |
+
+
+### Framework versions
+
+- Transformers 4.43.3
+- Pytorch 2.4.0+cu118
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

@@ -1,84 +1,84 @@
-{
-  "_name_or_path": "bert-base-cased",
-  "architectures": [
-    "BertForTokenClassification"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
-  "gradient_checkpointing": false,
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "id2label": {
-    "0": "B-Area",
-    "1": "B-Exp",
-    "2": "B-Features",
-    "3": "B-HackOrg",
-    "4": "B-Idus",
-    "5": "B-OffAct",
-    "6": "B-Org",
-    "7": "B-Purp",
-    "8": "B-SamFile",
-    "9": "B-SecTeam",
-    "10": "B-Time",
-    "11": "B-Tool",
-    "12": "B-Way",
-    "13": "I-Area",
-    "14": "I-Exp",
-    "15": "I-Features",
-    "16": "I-HackOrg",
-    "17": "I-Idus",
-    "18": "I-OffAct",
-    "19": "I-Org",
-    "20": "I-Purp",
-    "21": "I-SamFile",
-    "22": "I-SecTeam",
-    "23": "I-Time",
-    "24": "I-Tool",
-    "25": "I-Way",
-    "26": "O"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "B-Area": 0,
-    "B-Exp": 1,
-    "B-Features": 2,
-    "B-HackOrg": 3,
-    "B-Idus": 4,
-    "B-OffAct": 5,
-    "B-Org": 6,
-    "B-Purp": 7,
-    "B-SamFile": 8,
-    "B-SecTeam": 9,
-    "B-Time": 10,
-    "B-Tool": 11,
-    "B-Way": 12,
-    "I-Area": 13,
-    "I-Exp": 14,
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-    "I-Purp": 20,
-    "I-SamFile": 21,
-    "I-SecTeam": 22,
-    "I-Time": 23,
-    "I-Tool": 24,
-    "I-Way": 25,
-    "O": 26
-  },
-  "layer_norm_eps": 1e-12,
-  "max_position_embeddings": 512,
-  "model_type": "bert",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "pad_token_id": 0,
-  "position_embedding_type": "absolute",
-  "torch_dtype": "float32",
-  "transformers_version": "4.42.4",
-  "type_vocab_size": 2,
-  "use_cache": true,
-  "vocab_size": 28996
-}
+{
+  "_name_or_path": "bert-base-cased",
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "B-Area",
+    "1": "B-Exp",
+    "2": "B-Features",
+    "3": "B-HackOrg",
+    "4": "B-Idus",
+    "5": "B-OffAct",
+    "6": "B-Org",
+    "7": "B-Purp",
+    "8": "B-SamFile",
+    "9": "B-SecTeam",
+    "10": "B-Time",
+    "11": "B-Tool",
+    "12": "B-Way",
+    "13": "I-Area",
+    "14": "I-Exp",
+    "15": "I-Features",
+    "16": "I-HackOrg",
+    "17": "I-Idus",
+    "18": "I-OffAct",
+    "19": "I-Org",
+    "20": "I-Purp",
+    "21": "I-SamFile",
+    "22": "I-SecTeam",
+    "23": "I-Time",
+    "24": "I-Tool",
+    "25": "I-Way",
+    "26": "O"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-Area": 0,
+    "B-Exp": 1,
+    "B-Features": 2,
+    "B-HackOrg": 3,
+    "B-Idus": 4,
+    "B-OffAct": 5,
+    "B-Org": 6,
+    "B-Purp": 7,
+    "B-SamFile": 8,
+    "B-SecTeam": 9,
+    "B-Time": 10,
+    "B-Tool": 11,
+    "B-Way": 12,
+    "I-Area": 13,
+    "I-Exp": 14,
+    "I-Features": 15,
+    "I-HackOrg": 16,
+    "I-Idus": 17,
+    "I-OffAct": 18,
+    "I-Org": 19,
+    "I-Purp": 20,
+    "I-SamFile": 21,
+    "I-SecTeam": 22,
+    "I-Time": 23,
+    "I-Tool": 24,
+    "I-Way": 25,
+    "O": 26
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.43.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 28996
+}

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tokenizer_config.json

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+}

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