End of training

README.md

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+---
+base_model: dccuchile/bert-base-spanish-wwm-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: ABL_trad_2f
+  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. -->
+
+# ABL_trad_2f
+
+This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6589
+- Accuracy: 0.7588
+- F1: 0.7579
+
+## 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: 5e-06
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 12
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
+| 0.7767        | 1.0   | 4683  | 0.7649          | 0.6539   | 0.6532 |
+| 0.6994        | 2.0   | 9366  | 0.7013          | 0.6922   | 0.6907 |
+| 0.6426        | 3.0   | 14049 | 0.6683          | 0.7106   | 0.7092 |
+| 0.5984        | 4.0   | 18732 | 0.6440          | 0.7226   | 0.7218 |
+| 0.5734        | 5.0   | 23415 | 0.6329          | 0.7301   | 0.7291 |
+| 0.5274        | 6.0   | 28098 | 0.6229          | 0.7364   | 0.7348 |
+| 0.5195        | 7.0   | 32781 | 0.6193          | 0.7444   | 0.7430 |
+| 0.4795        | 8.0   | 37464 | 0.6272          | 0.7486   | 0.7468 |
+| 0.4548        | 9.0   | 42147 | 0.6228          | 0.7498   | 0.7481 |
+| 0.4284        | 10.0  | 46830 | 0.6356          | 0.7534   | 0.7522 |
+| 0.4068        | 11.0  | 51513 | 0.6494          | 0.7550   | 0.7541 |
+| 0.3788        | 12.0  | 56196 | 0.6589          | 0.7588   | 0.7579 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

config.json

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+{
+  "_name_or_path": "dccuchile/bert-base-spanish-wwm-cased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "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": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2
+  },
+  "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",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 31002
+}

model.safetensors

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runs/Sep25_03-12-14_PcJavierOmen/events.out.tfevents.1727226735.PcJavierOmen.25252.0

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runs/Sep25_03-12-14_PcJavierOmen/events.out.tfevents.1727239093.PcJavierOmen.25252.1

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special_tokens_map.json

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+{
+  "cls_token": {
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+    "single_word": false
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+    "lstrip": false,
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+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
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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": false,
+  "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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