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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: cc-by-4.0
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+ base_model: dccuchile/tulio-chilean-spanish-bert
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: Gestionabilidad-v3_batch32
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # Gestionabilidad-v3_batch32
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+
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+ This model is a fine-tuned version of [dccuchile/tulio-chilean-spanish-bert](https://huggingface.co/dccuchile/tulio-chilean-spanish-bert) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1858
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+ - Accuracy: 0.9298
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+ - Precision: 0.9300
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+ - Recall: 0.9298
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+ - F1: 0.9296
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:------:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.283 | 0.2289 | 500 | 0.2429 | 0.9044 | 0.9072 | 0.9044 | 0.9048 |
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+ | 0.2275 | 0.4579 | 1000 | 0.2073 | 0.9185 | 0.9185 | 0.9185 | 0.9183 |
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+ | 0.2066 | 0.6868 | 1500 | 0.1900 | 0.9187 | 0.9202 | 0.9187 | 0.9181 |
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+ | 0.1949 | 0.9158 | 2000 | 0.2105 | 0.9194 | 0.9213 | 0.9194 | 0.9187 |
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+ | 0.1657 | 1.1447 | 2500 | 0.1920 | 0.9263 | 0.9270 | 0.9263 | 0.9259 |
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+ | 0.1502 | 1.3736 | 3000 | 0.2021 | 0.9280 | 0.9279 | 0.9280 | 0.9279 |
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+ | 0.1412 | 1.6026 | 3500 | 0.1858 | 0.9298 | 0.9300 | 0.9298 | 0.9296 |
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+ | 0.1477 | 1.8315 | 4000 | 0.1950 | 0.9300 | 0.9304 | 0.9300 | 0.9301 |
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+ | 0.1296 | 2.0604 | 4500 | 0.2188 | 0.9303 | 0.9304 | 0.9303 | 0.9304 |
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+ | 0.1004 | 2.2894 | 5000 | 0.2367 | 0.9304 | 0.9305 | 0.9304 | 0.9305 |
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+ | 0.0958 | 2.5183 | 5500 | 0.2294 | 0.9305 | 0.9305 | 0.9305 | 0.9303 |
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+ | 0.1003 | 2.7473 | 6000 | 0.2394 | 0.9293 | 0.9299 | 0.9293 | 0.9290 |
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+ | 0.1029 | 2.9762 | 6500 | 0.2294 | 0.9321 | 0.9320 | 0.9321 | 0.9320 |
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+ | 0.0696 | 3.2051 | 7000 | 0.2727 | 0.9324 | 0.9324 | 0.9324 | 0.9322 |
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+ | 0.0619 | 3.4341 | 7500 | 0.2672 | 0.9287 | 0.9301 | 0.9287 | 0.9289 |
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+ | 0.0627 | 3.6630 | 8000 | 0.2897 | 0.9326 | 0.9329 | 0.9326 | 0.9327 |
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+ | 0.0639 | 3.8919 | 8500 | 0.2970 | 0.9322 | 0.9322 | 0.9322 | 0.9322 |
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+ | 0.0549 | 4.1209 | 9000 | 0.3230 | 0.9321 | 0.9322 | 0.9321 | 0.9321 |
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+ | 0.0409 | 4.3498 | 9500 | 0.3722 | 0.9313 | 0.9317 | 0.9313 | 0.9314 |
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+ | 0.0388 | 4.5788 | 10000 | 0.3326 | 0.9333 | 0.9335 | 0.9333 | 0.9333 |
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+ | 0.0373 | 4.8077 | 10500 | 0.3565 | 0.9332 | 0.9335 | 0.9332 | 0.9333 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.3
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.3.2
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+ - Tokenizers 0.21.0
config.json ADDED
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+ {
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+ "_name_or_path": "dccuchile/tulio-chilean-spanish-bert",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "output_past": true,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.48.3",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 31002
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+ }
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