End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+datasets:
+- conll2002
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-ner-cfv
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2002
+      type: conll2002
+      config: es
+      split: validation
+      args: es
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.807683615819209
+    - name: Recall
+      type: recall
+      value: 0.8212316176470589
+    - name: F1
+      type: f1
+      value: 0.8144012760624361
+    - name: Accuracy
+      type: accuracy
+      value: 0.974075543714453
+---
+
+<!-- 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-cfv
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2002 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1851
+- Precision: 0.8077
+- Recall: 0.8212
+- F1: 0.8144
+- Accuracy: 0.9741
+
+## 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: 4e-05
+- train_batch_size: 24
+- eval_batch_size: 24
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 17
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 347  | 0.1278          | 0.7284    | 0.7475 | 0.7378 | 0.9646   |
+| 0.1176        | 2.0   | 694  | 0.1212          | 0.7509    | 0.7806 | 0.7654 | 0.9681   |
+| 0.0453        | 3.0   | 1041 | 0.1156          | 0.8062    | 0.8116 | 0.8089 | 0.9730   |
+| 0.0453        | 4.0   | 1388 | 0.1270          | 0.8081    | 0.8031 | 0.8056 | 0.9720   |
+| 0.0233        | 5.0   | 1735 | 0.1298          | 0.8145    | 0.8231 | 0.8187 | 0.9746   |
+| 0.0145        | 6.0   | 2082 | 0.1431          | 0.7950    | 0.8091 | 0.8020 | 0.9728   |
+| 0.0145        | 7.0   | 2429 | 0.1501          | 0.8103    | 0.8166 | 0.8135 | 0.9734   |
+| 0.009         | 8.0   | 2776 | 0.1553          | 0.8118    | 0.8157 | 0.8138 | 0.9738   |
+| 0.0061        | 9.0   | 3123 | 0.1572          | 0.7891    | 0.8084 | 0.7986 | 0.9720   |
+| 0.0061        | 10.0  | 3470 | 0.1589          | 0.8142    | 0.8196 | 0.8169 | 0.9739   |
+| 0.005         | 11.0  | 3817 | 0.1671          | 0.8092    | 0.8148 | 0.8120 | 0.9733   |
+| 0.0032        | 12.0  | 4164 | 0.1716          | 0.8066    | 0.8139 | 0.8102 | 0.9733   |
+| 0.0031        | 13.0  | 4511 | 0.1767          | 0.8025    | 0.8169 | 0.8096 | 0.9731   |
+| 0.0031        | 14.0  | 4858 | 0.1756          | 0.8096    | 0.8217 | 0.8156 | 0.9741   |
+| 0.0023        | 15.0  | 5205 | 0.1845          | 0.8109    | 0.8157 | 0.8133 | 0.9739   |
+| 0.0018        | 16.0  | 5552 | 0.1850          | 0.8090    | 0.8203 | 0.8146 | 0.9739   |
+| 0.0018        | 17.0  | 5899 | 0.1851          | 0.8077    | 0.8212 | 0.8144 | 0.9741   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

config.json

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+{
+  "_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": "O",
+    "1": "B-PER",
+    "2": "I-PER",
+    "3": "B-ORG",
+    "4": "I-ORG",
+    "5": "B-LOC",
+    "6": "I-LOC",
+    "7": "B-MISC",
+    "8": "I-MISC"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-LOC": 5,
+    "B-MISC": 7,
+    "B-ORG": 3,
+    "B-PER": 1,
+    "I-LOC": 6,
+    "I-MISC": 8,
+    "I-ORG": 4,
+    "I-PER": 2,
+    "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": "4.41.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 28996
+}

model.safetensors

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runs/Jun06_02-30-26_9d57eae5ff74/events.out.tfevents.1717641030.9d57eae5ff74.448.0

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special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "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

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