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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: edyfjm07/distilbert-base-uncased-QA4-finetuned-squad-es |
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results: [] |
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datasets: |
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- edyfjm07/squad_indicaciones_es |
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language: |
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- es |
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metrics: |
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- rouge |
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- recall |
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- accuracy |
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- f1 |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# edyfjm07/distilbert-base-uncased-QA4-finetuned-squad-es |
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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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- Train Loss: 0.0931 |
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- Train End Logits Accuracy: 0.9559 |
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- Train Start Logits Accuracy: 0.9685 |
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- Validation Loss: 1.2632 |
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- Validation End Logits Accuracy: 0.8088 |
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- Validation Start Logits Accuracy: 0.8088 |
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- Epoch: 45 |
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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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- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 5474, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch | |
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|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:| |
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| 3.8949 | 0.1733 | 0.1891 | 2.4981 | 0.3918 | 0.3981 | 0 | |
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| 2.0479 | 0.4097 | 0.4811 | 1.6575 | 0.4890 | 0.6113 | 1 | |
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| 1.4343 | 0.5599 | 0.6166 | 1.3371 | 0.5768 | 0.6426 | 2 | |
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| 1.0892 | 0.6313 | 0.6891 | 1.1850 | 0.6677 | 0.6865 | 3 | |
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| 0.9172 | 0.6870 | 0.7405 | 1.1305 | 0.6771 | 0.7335 | 4 | |
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| 0.7470 | 0.7258 | 0.7910 | 1.0674 | 0.7147 | 0.7524 | 5 | |
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| 0.6728 | 0.7426 | 0.8088 | 1.0843 | 0.7116 | 0.7680 | 6 | |
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| 0.5989 | 0.7721 | 0.8403 | 1.0787 | 0.7304 | 0.7649 | 7 | |
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| 0.4988 | 0.8057 | 0.8582 | 1.1091 | 0.7398 | 0.7618 | 8 | |
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| 0.4674 | 0.8214 | 0.8540 | 1.1150 | 0.7367 | 0.7774 | 9 | |
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| 0.4173 | 0.8256 | 0.8782 | 1.1434 | 0.7335 | 0.7774 | 10 | |
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| 0.3804 | 0.8319 | 0.8897 | 1.1256 | 0.7335 | 0.7900 | 11 | |
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| 0.3831 | 0.8456 | 0.8834 | 1.1614 | 0.7429 | 0.7931 | 12 | |
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| 0.3325 | 0.8550 | 0.9097 | 1.1519 | 0.7429 | 0.7900 | 13 | |
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| 0.3115 | 0.8739 | 0.9076 | 1.1423 | 0.7586 | 0.7868 | 14 | |
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| 0.2860 | 0.8792 | 0.9160 | 1.1335 | 0.7649 | 0.8025 | 15 | |
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| 0.2751 | 0.8834 | 0.9181 | 1.1135 | 0.7712 | 0.8119 | 16 | |
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| 0.2441 | 0.8918 | 0.9296 | 1.1771 | 0.7524 | 0.7900 | 17 | |
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| 0.2342 | 0.9044 | 0.9370 | 1.1433 | 0.7680 | 0.8088 | 18 | |
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| 0.2049 | 0.9254 | 0.9391 | 1.1689 | 0.7680 | 0.7994 | 19 | |
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| 0.2029 | 0.9170 | 0.9475 | 1.1659 | 0.8025 | 0.8150 | 20 | |
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| 0.1939 | 0.9170 | 0.9422 | 1.2030 | 0.7712 | 0.8150 | 21 | |
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| 0.1787 | 0.9202 | 0.9548 | 1.2073 | 0.7806 | 0.8056 | 22 | |
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| 0.2013 | 0.9233 | 0.9485 | 1.1615 | 0.7962 | 0.7994 | 23 | |
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| 0.1821 | 0.9349 | 0.9443 | 1.1657 | 0.7806 | 0.8088 | 24 | |
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| 0.1683 | 0.9328 | 0.9464 | 1.1684 | 0.7994 | 0.8088 | 25 | |
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| 0.1568 | 0.9286 | 0.9580 | 1.1909 | 0.7900 | 0.8056 | 26 | |
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| 0.1536 | 0.9244 | 0.9590 | 1.2054 | 0.7868 | 0.8182 | 27 | |
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| 0.1221 | 0.9485 | 0.9601 | 1.1996 | 0.7806 | 0.8088 | 28 | |
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| 0.1373 | 0.9349 | 0.9601 | 1.2201 | 0.7806 | 0.8056 | 29 | |
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| 0.1334 | 0.9443 | 0.9569 | 1.2531 | 0.7868 | 0.8025 | 30 | |
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| 0.1335 | 0.9422 | 0.9569 | 1.2030 | 0.7962 | 0.8088 | 31 | |
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| 0.1157 | 0.9485 | 0.9590 | 1.2142 | 0.7931 | 0.8088 | 32 | |
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| 0.1209 | 0.9475 | 0.9590 | 1.2215 | 0.7743 | 0.7994 | 33 | |
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| 0.1149 | 0.9548 | 0.9653 | 1.2125 | 0.7806 | 0.8056 | 34 | |
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| 0.1048 | 0.9538 | 0.9674 | 1.2632 | 0.7900 | 0.8056 | 35 | |
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| 0.1056 | 0.9475 | 0.9706 | 1.2485 | 0.7931 | 0.8088 | 36 | |
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| 0.0964 | 0.9653 | 0.9685 | 1.2468 | 0.7900 | 0.8088 | 37 | |
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| 0.1000 | 0.9559 | 0.9664 | 1.2422 | 0.7962 | 0.8056 | 38 | |
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| 0.0989 | 0.9601 | 0.9653 | 1.2620 | 0.8025 | 0.8056 | 39 | |
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| 0.1024 | 0.9590 | 0.9674 | 1.2528 | 0.7994 | 0.8056 | 40 | |
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| 0.0917 | 0.9548 | 0.9716 | 1.2506 | 0.7931 | 0.8088 | 41 | |
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| 0.0913 | 0.9580 | 0.9685 | 1.2538 | 0.8025 | 0.8056 | 42 | |
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| 0.0923 | 0.9664 | 0.9632 | 1.2619 | 0.8025 | 0.8056 | 43 | |
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| 0.0921 | 0.9559 | 0.9643 | 1.2621 | 0.8056 | 0.8088 | 44 | |
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| 0.0931 | 0.9559 | 0.9685 | 1.2632 | 0.8088 | 0.8088 | 45 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
