End of training
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README.md
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---
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library_name: transformers
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base_model: distilbert-base-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: mi-super-modelo
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results: []
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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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# mi-super-modelo
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3257
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- Accuracy: 0.865
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 8
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- eval_batch_size: 8
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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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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.7019 | 0.04 | 5 | 0.6916 | 0.51 |
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| 0.7006 | 0.08 | 10 | 0.6860 | 0.495 |
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| 0.7015 | 0.12 | 15 | 0.6802 | 0.58 |
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| 0.6842 | 0.16 | 20 | 0.6756 | 0.525 |
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| 0.658 | 0.2 | 25 | 0.6492 | 0.595 |
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| 0.6329 | 0.24 | 30 | 0.5335 | 0.855 |
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| 0.4345 | 0.28 | 35 | 0.4493 | 0.825 |
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| 0.3086 | 0.32 | 40 | 0.3973 | 0.84 |
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| 0.4788 | 0.36 | 45 | 0.3747 | 0.855 |
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| 0.6449 | 0.4 | 50 | 0.4614 | 0.8 |
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| 0.2355 | 0.44 | 55 | 0.3603 | 0.855 |
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| 0.4233 | 0.48 | 60 | 0.4841 | 0.8 |
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| 0.5185 | 0.52 | 65 | 0.5940 | 0.755 |
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| 0.3089 | 0.56 | 70 | 0.3760 | 0.87 |
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| 0.3867 | 0.6 | 75 | 0.3636 | 0.86 |
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| 0.3289 | 0.64 | 80 | 0.3339 | 0.885 |
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| 0.5774 | 0.68 | 85 | 0.3070 | 0.875 |
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| 0.3258 | 0.72 | 90 | 0.4532 | 0.8 |
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| 0.5363 | 0.76 | 95 | 0.3687 | 0.86 |
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| 0.4099 | 0.8 | 100 | 0.2847 | 0.88 |
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| 0.2841 | 0.84 | 105 | 0.3147 | 0.885 |
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| 0.3949 | 0.88 | 110 | 0.3424 | 0.855 |
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| 0.3056 | 0.92 | 115 | 0.3620 | 0.835 |
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| 0.4219 | 0.96 | 120 | 0.3437 | 0.855 |
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| 0.3343 | 1.0 | 125 | 0.3257 | 0.865 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.1+cpu
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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