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End of training

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README.md ADDED
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+ ---
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+ base_model: dccuchile/distilbert-base-spanish-uncased
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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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+ model-index:
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+ - name: Prototipo_3_EMI
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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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+ # Prototipo_3_EMI
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+
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+ This model is a fine-tuned version of [dccuchile/distilbert-base-spanish-uncased](https://huggingface.co/dccuchile/distilbert-base-spanish-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2540
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+ - Accuracy: 0.5423
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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: 3e-05
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+ - train_batch_size: 24
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+ - eval_batch_size: 24
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 250
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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 |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 1.2186 | 0.1778 | 200 | 1.1556 | 0.4803 |
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+ | 1.1345 | 0.3556 | 400 | 1.0663 | 0.525 |
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+ | 1.102 | 0.5333 | 600 | 1.0479 | 0.5293 |
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+ | 1.1325 | 0.7111 | 800 | 1.0483 | 0.5353 |
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+ | 1.1211 | 0.8889 | 1000 | 1.0337 | 0.521 |
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+ | 0.9736 | 1.0667 | 1200 | 1.0006 | 0.5503 |
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+ | 0.9428 | 1.2444 | 1400 | 1.0214 | 0.5523 |
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+ | 0.9095 | 1.4222 | 1600 | 1.0174 | 0.555 |
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+ | 0.9806 | 1.6 | 1800 | 1.0155 | 0.5527 |
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+ | 0.969 | 1.7778 | 2000 | 1.0043 | 0.5547 |
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+ | 0.9112 | 1.9556 | 2200 | 1.0050 | 0.5537 |
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+ | 0.7557 | 2.1333 | 2400 | 1.0496 | 0.5607 |
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+ | 0.8212 | 2.3111 | 2600 | 1.0494 | 0.5597 |
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+ | 0.7695 | 2.4889 | 2800 | 1.0510 | 0.5687 |
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+ | 0.7648 | 2.6667 | 3000 | 1.0513 | 0.5603 |
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+ | 0.8232 | 2.8444 | 3200 | 1.0316 | 0.563 |
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+ | 0.6288 | 3.0222 | 3400 | 1.0883 | 0.5503 |
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+ | 0.6736 | 3.2 | 3600 | 1.1232 | 0.548 |
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+ | 0.682 | 3.3778 | 3800 | 1.1695 | 0.543 |
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+ | 0.6682 | 3.5556 | 4000 | 1.1608 | 0.5427 |
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+ | 0.6516 | 3.7333 | 4200 | 1.1636 | 0.545 |
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+ | 0.6731 | 3.9111 | 4400 | 1.1694 | 0.5403 |
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+ | 0.5388 | 4.0889 | 4600 | 1.2120 | 0.544 |
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+ | 0.5663 | 4.2667 | 4800 | 1.2278 | 0.544 |
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+ | 0.5579 | 4.4444 | 5000 | 1.2439 | 0.538 |
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+ | 0.5216 | 4.6222 | 5200 | 1.2507 | 0.5427 |
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+ | 0.4634 | 4.8 | 5400 | 1.2531 | 0.5393 |
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+ | 0.5359 | 4.9778 | 5600 | 1.2540 | 0.5423 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.1
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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