End of training

README.md

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+---
+base_model: dccuchile/bert-base-spanish-wwm-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-base-spanish-wwm-uncased-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-base-spanish-wwm-uncased-ner
+
+This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3905
+- Precision: 0.8768
+- Recall: 0.9067
+- F1: 0.8915
+- Accuracy: 0.9376
+
+## 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: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 280  | 0.2690          | 0.8236    | 0.8578 | 0.8403 | 0.9268   |
+| 0.3996        | 2.0   | 560  | 0.2917          | 0.8116    | 0.8681 | 0.8389 | 0.9180   |
+| 0.3996        | 3.0   | 840  | 0.2715          | 0.8495    | 0.8696 | 0.8594 | 0.9319   |
+| 0.118         | 4.0   | 1120 | 0.2914          | 0.8567    | 0.9037 | 0.8796 | 0.9370   |
+| 0.118         | 5.0   | 1400 | 0.3040          | 0.8454    | 0.8993 | 0.8715 | 0.9330   |
+| 0.0608        | 6.0   | 1680 | 0.2979          | 0.8631    | 0.8963 | 0.8794 | 0.9359   |
+| 0.0608        | 7.0   | 1960 | 0.3376          | 0.8653    | 0.8948 | 0.8798 | 0.9322   |
+| 0.0353        | 8.0   | 2240 | 0.3283          | 0.8622    | 0.9081 | 0.8846 | 0.9370   |
+| 0.0236        | 9.0   | 2520 | 0.3584          | 0.8575    | 0.9007 | 0.8786 | 0.9351   |
+| 0.0236        | 10.0  | 2800 | 0.3891          | 0.8813    | 0.9022 | 0.8917 | 0.9346   |
+| 0.0155        | 11.0  | 3080 | 0.3678          | 0.8764    | 0.9037 | 0.8899 | 0.9381   |
+| 0.0155        | 12.0  | 3360 | 0.3736          | 0.8759    | 0.9096 | 0.8924 | 0.9386   |
+| 0.0123        | 13.0  | 3640 | 0.4030          | 0.8721    | 0.8993 | 0.8855 | 0.9349   |
+| 0.0123        | 14.0  | 3920 | 0.3890          | 0.8768    | 0.9067 | 0.8915 | 0.9373   |
+| 0.0123        | 15.0  | 4200 | 0.3905          | 0.8768    | 0.9067 | 0.8915 | 0.9376   |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "dccuchile/bert-base-spanish-wwm-uncased",
+  "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-Anatomical_Entity",
+    "10": "I-Location",
+    "11": "B-Type_of_measure",
+    "12": "I-Type_of_measure",
+    "13": "B-Measure",
+    "14": "I-Measure",
+    "15": "B-Degree",
+    "16": "I-Degree",
+    "17": "B-ConditionalTemporal",
+    "18": "I-ConditionalTemporal",
+    "2": "I-Anatomical_Entity",
+    "3": "B-Finding",
+    "4": "I-Finding",
+    "5": "B-Uncertainty",
+    "6": "I-Uncertainty",
+    "7": "B-Negation",
+    "8": "I-Negation",
+    "9": "B-Location"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-Anatomical_Entity": "1",
+    "B-ConditionalTemporal": "17",
+    "B-Degree": "15",
+    "B-Finding": "3",
+    "B-Location": "9",
+    "B-Measure": "13",
+    "B-Negation": "7",
+    "B-Type_of_measure": "11",
+    "B-Uncertainty": "5",
+    "I-Anatomical_Entity": "2",
+    "I-ConditionalTemporal": "18",
+    "I-Degree": "16",
+    "I-Finding": "4",
+    "I-Location": "10",
+    "I-Measure": "14",
+    "I-Negation": "8",
+    "I-Type_of_measure": "12",
+    "I-Uncertainty": "6",
+    "O": "0"
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 31002
+}

model.safetensors

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runs/Jun02_17-55-33_167d16a24718/events.out.tfevents.1717350934.167d16a24718.192.0

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special_tokens_map.json

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+{
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+    "content": "[CLS]",
+    "lstrip": false,
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+    "rstrip": false,
+    "single_word": false
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+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
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+      "single_word": false,
+      "special": true
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+      "lstrip": false,
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+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": false,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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