End of training

README.md

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+---
+library_name: transformers
+license: cc-by-4.0
+base_model: M4rt0no/Gestionabilidad-v3_batch32
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: Gestionabilidad-v4_batch32
+  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. -->
+
+# Gestionabilidad-v4_batch32
+
+This model is a fine-tuned version of [M4rt0no/Gestionabilidad-v3_batch32](https://huggingface.co/M4rt0no/Gestionabilidad-v3_batch32) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5671
+- Accuracy: 0.8731
+- Precision: 0.8726
+- Recall: 0.8731
+- F1: 0.8691
+
+## 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-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.083         | 0.7220 | 400  | 0.6704          | 0.8660   | 0.8641    | 0.8660 | 0.8628 |
+| 0.1806        | 1.4440 | 800  | 0.5671          | 0.8731   | 0.8726    | 0.8731 | 0.8691 |
+| 0.1207        | 2.1661 | 1200 | 0.6259          | 0.8800   | 0.8783    | 0.8800 | 0.8782 |
+| 0.0571        | 2.8881 | 1600 | 0.7081          | 0.8702   | 0.8711    | 0.8702 | 0.8706 |
+| 0.0303        | 3.6101 | 2000 | 0.7597          | 0.8734   | 0.8734    | 0.8734 | 0.8734 |
+| 0.0199        | 4.3321 | 2400 | 0.7955          | 0.8818   | 0.8803    | 0.8818 | 0.8803 |
+
+
+### Framework versions
+
+- Transformers 4.48.3
+- Pytorch 2.5.1+cu124
+- Datasets 3.3.2
+- Tokenizers 0.21.0

config.json

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+{
+  "_name_or_path": "M4rt0no/Gestionabilidad-v3_batch32",
+  "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,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "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": "4.48.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 31002
+}

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