Finished training

README.md

@@ -0,0 +1,72 @@
+---
+license: mit
+base_model: google-bert/bert-base-german-cased
+tags:
+- generated_from_trainer
+model-index:
+- name: bert-mapa-german
+  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-mapa-german
+
+This model is a fine-tuned version of [google-bert/bert-base-german-cased](https://huggingface.co/google-bert/bert-base-german-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0325
+- Address: {'precision': 0.5882352941176471, 'recall': 0.6666666666666666, 'f1': 0.625, 'number': 15}
+- Age: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
+- Amount: {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1}
+- Date: {'precision': 0.9454545454545454, 'recall': 0.9454545454545454, 'f1': 0.9454545454545454, 'number': 55}
+- Name: {'precision': 0.7, 'recall': 0.9545454545454546, 'f1': 0.8076923076923077, 'number': 22}
+- Organisation: {'precision': 0.5405405405405406, 'recall': 0.6451612903225806, 'f1': 0.588235294117647, 'number': 31}
+- Person: {'precision': 0.5384615384615384, 'recall': 0.5, 'f1': 0.5185185185185186, 'number': 14}
+- Role: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
+- Overall Precision: 0.7255
+- Overall Recall: 0.7817
+- Overall F1: 0.7525
+- Overall Accuracy: 0.9912
+
+## 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: 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: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Address                                                                                    | Amount                                                    | Date                                                                                                    | Marital status                                            | Name                                                                                                    | Organisation                                                                               | Person                                                                                                  | Profession                                                | Role                                                      | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------------------------------------:|:---------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| No log        | 1.0   | 218  | 0.0607          | {'precision': 0.5882352941176471, 'recall': 0.6666666666666666, 'f1': 0.625, 'number': 15} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3} | {'precision': 0.851063829787234, 'recall': 0.9090909090909091, 'f1': 0.8791208791208791, 'number': 44}  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.76, 'recall': 0.9047619047619048, 'f1': 0.8260869565217391, 'number': 21}               | {'precision': 0.4915254237288136, 'recall': 0.725, 'f1': 0.5858585858585859, 'number': 40} | {'precision': 0.5, 'recall': 0.6153846153846154, 'f1': 0.5517241379310345, 'number': 13}                | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | 0.6527            | 0.7786         | 0.7101     | 0.9859           |
+| No log        | 2.0   | 436  | 0.0479          | {'precision': 0.65, 'recall': 0.8666666666666667, 'f1': 0.7428571428571429, 'number': 15}  | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3} | {'precision': 0.8958333333333334, 'recall': 0.9772727272727273, 'f1': 0.9347826086956522, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.6774193548387096, 'recall': 1.0, 'f1': 0.8076923076923077, 'number': 21}                | {'precision': 0.5897435897435898, 'recall': 0.575, 'f1': 0.5822784810126582, 'number': 40} | {'precision': 0.7857142857142857, 'recall': 0.8461538461538461, 'f1': 0.8148148148148148, 'number': 13} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | 0.7355            | 0.8143         | 0.7729     | 0.9896           |
+| 0.116         | 3.0   | 654  | 0.0414          | {'precision': 0.65, 'recall': 0.8666666666666667, 'f1': 0.7428571428571429, 'number': 15}  | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3} | {'precision': 0.8958333333333334, 'recall': 0.9772727272727273, 'f1': 0.9347826086956522, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.7407407407407407, 'recall': 0.9523809523809523, 'f1': 0.8333333333333334, 'number': 21} | {'precision': 0.725, 'recall': 0.725, 'f1': 0.7250000000000001, 'number': 40}              | {'precision': 0.6666666666666666, 'recall': 0.7692307692307693, 'f1': 0.7142857142857142, 'number': 13} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | 0.7712            | 0.8429         | 0.8055     | 0.9908           |
+| 0.116         | 4.0   | 872  | 0.0421          | {'precision': 0.65, 'recall': 0.8666666666666667, 'f1': 0.7428571428571429, 'number': 15}  | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3} | {'precision': 0.8958333333333334, 'recall': 0.9772727272727273, 'f1': 0.9347826086956522, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.8, 'recall': 0.9523809523809523, 'f1': 0.8695652173913043, 'number': 21}                | {'precision': 0.6818181818181818, 'recall': 0.75, 'f1': 0.7142857142857143, 'number': 40}  | {'precision': 0.8571428571428571, 'recall': 0.9230769230769231, 'f1': 0.888888888888889, 'number': 13}  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | 0.7857            | 0.8643         | 0.8231     | 0.9917           |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.1.0+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

config.json

@@ -0,0 +1,79 @@
+{
+  "_name_or_path": "google-bert/bert-base-german-cased",
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "O",
+    "1": "B-ADDRESS",
+    "2": "I-ADDRESS",
+    "3": "B-DATE",
+    "4": "I-DATE",
+    "5": "B-ORGANISATION",
+    "6": "I-ORGANISATION",
+    "7": "B-NAME",
+    "8": "I-NAME",
+    "9": "B-PERSON",
+    "10": "I-PERSON",
+    "11": "B-ROLE",
+    "12": "I-ROLE",
+    "13": "B-PROFESSION",
+    "14": "I-PROFESSION",
+    "15": "B-AMOUNT",
+    "16": "I-AMOUNT",
+    "17": "B-AGE",
+    "18": "I-AGE",
+    "19": "B-MARITAL STATUS",
+    "20": "I-MARITAL STATUS",
+    "21": "B-ETHNIC CATEGORY",
+    "22": "I-ETHNIC CATEGORY",
+    "23": "B-NATIONALITY",
+    "24": "I-NATIONALITY"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-ADDRESS": 1,
+    "B-AGE": 17,
+    "B-AMOUNT": 15,
+    "B-DATE": 3,
+    "B-ETHNIC CATEGORY": 21,
+    "B-MARITAL STATUS": 19,
+    "B-NAME": 7,
+    "B-NATIONALITY": 23,
+    "B-ORGANISATION": 5,
+    "B-PERSON": 9,
+    "B-PROFESSION": 13,
+    "B-ROLE": 11,
+    "I-ADDRESS": 2,
+    "I-AGE": 18,
+    "I-AMOUNT": 16,
+    "I-DATE": 4,
+    "I-ETHNIC CATEGORY": 22,
+    "I-MARITAL STATUS": 20,
+    "I-NAME": 8,
+    "I-NATIONALITY": 24,
+    "I-ORGANISATION": 6,
+    "I-PERSON": 10,
+    "I-PROFESSION": 14,
+    "I-ROLE": 12,
+    "O": 0
+  },
+  "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": "4.40.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30000
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9057eb525021c8fbd2d8c9e244f581bc9edf48d5bed2717d07dc6962020d6cd7
+size 434063252

special_tokens_map.json

@@ -0,0 +1,7 @@
+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

@@ -0,0 +1,55 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "4": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "5": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ff9df7507025cdc300d4ca63aef319fb27233fa244fc064689e7f53443c8ec24
+size 4984