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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-QA2-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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- f1 |
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- recall |
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- accuracy |
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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-QA2-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: 0.0138 |
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- Train End Logits Accuracy: 0.9947 |
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- Train Start Logits Accuracy: 1.0 |
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- Validation Loss: 1.7511 |
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- Validation End Logits Accuracy: 0.7931 |
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- Validation Start Logits Accuracy: 0.7994 |
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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': 0.0001, '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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| 2.3428 | 0.4160 | 0.4317 | 1.3438 | 0.5611 | 0.6458 | 0 | |
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| 1.1526 | 0.6261 | 0.6397 | 1.0597 | 0.6677 | 0.7429 | 1 | |
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| 0.7612 | 0.7269 | 0.7647 | 1.0245 | 0.7210 | 0.7806 | 2 | |
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| 0.5528 | 0.7836 | 0.8319 | 1.2436 | 0.7116 | 0.7712 | 3 | |
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| 0.4667 | 0.8340 | 0.8435 | 1.0705 | 0.7524 | 0.7555 | 4 | |
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| 0.3834 | 0.8813 | 0.8687 | 1.1209 | 0.7586 | 0.7712 | 5 | |
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| 0.3678 | 0.8634 | 0.8876 | 1.2341 | 0.7618 | 0.7649 | 6 | |
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| 0.2555 | 0.9044 | 0.9181 | 1.1561 | 0.7649 | 0.8056 | 7 | |
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| 0.2151 | 0.9160 | 0.9328 | 1.0908 | 0.7931 | 0.7994 | 8 | |
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| 0.1855 | 0.9286 | 0.9475 | 1.2809 | 0.7994 | 0.7774 | 9 | |
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| 0.1654 | 0.9443 | 0.9454 | 1.3974 | 0.7837 | 0.7806 | 10 | |
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| 0.1282 | 0.9464 | 0.9517 | 1.4260 | 0.7774 | 0.7837 | 11 | |
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| 0.1313 | 0.9443 | 0.9601 | 1.4537 | 0.7900 | 0.7962 | 12 | |
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| 0.1301 | 0.9517 | 0.9590 | 1.1851 | 0.7774 | 0.8150 | 13 | |
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| 0.1089 | 0.9548 | 0.9590 | 1.2442 | 0.7774 | 0.8088 | 14 | |
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| 0.1023 | 0.9601 | 0.9622 | 1.4575 | 0.7931 | 0.7931 | 15 | |
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| 0.0956 | 0.9590 | 0.9685 | 1.5160 | 0.7837 | 0.7900 | 16 | |
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| 0.0712 | 0.9727 | 0.9737 | 1.5741 | 0.7900 | 0.8088 | 17 | |
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| 0.0752 | 0.9674 | 0.9790 | 1.4401 | 0.7931 | 0.7994 | 18 | |
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| 0.0604 | 0.9737 | 0.9779 | 1.6410 | 0.7962 | 0.8088 | 19 | |
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| 0.0497 | 0.9758 | 0.9821 | 1.5655 | 0.7962 | 0.8119 | 20 | |
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| 0.0668 | 0.9685 | 0.9811 | 1.3480 | 0.7806 | 0.7962 | 21 | |
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| 0.0567 | 0.9769 | 0.9800 | 1.3820 | 0.7900 | 0.8088 | 22 | |
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| 0.0550 | 0.9769 | 0.9832 | 1.3593 | 0.7806 | 0.8056 | 23 | |
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| 0.0399 | 0.9821 | 0.9884 | 1.5254 | 0.7868 | 0.7931 | 24 | |
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| 0.0320 | 0.9842 | 0.9874 | 1.5801 | 0.7868 | 0.7994 | 25 | |
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| 0.0296 | 0.9832 | 0.9884 | 1.6310 | 0.7962 | 0.7962 | 26 | |
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| 0.0307 | 0.9863 | 0.9926 | 1.4756 | 0.7774 | 0.7900 | 27 | |
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| 0.0254 | 0.9863 | 0.9895 | 1.7564 | 0.7774 | 0.7931 | 28 | |
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| 0.0255 | 0.9853 | 0.9937 | 1.6061 | 0.7774 | 0.7962 | 29 | |
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| 0.0214 | 0.9863 | 0.9937 | 1.7697 | 0.7712 | 0.8056 | 30 | |
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| 0.0283 | 0.9842 | 0.9863 | 1.8398 | 0.7806 | 0.7900 | 31 | |
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| 0.0182 | 0.9905 | 0.9926 | 1.8756 | 0.7837 | 0.7994 | 32 | |
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| 0.0252 | 0.9832 | 0.9947 | 1.8182 | 0.7837 | 0.7962 | 33 | |
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| 0.0222 | 0.9863 | 0.9947 | 1.7854 | 0.7837 | 0.7931 | 34 | |
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| 0.0216 | 0.9884 | 0.9947 | 1.5707 | 0.7931 | 0.8025 | 35 | |
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| 0.0161 | 0.9937 | 0.9916 | 1.7071 | 0.7806 | 0.8025 | 36 | |
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| 0.0146 | 0.9926 | 0.9926 | 1.7827 | 0.7868 | 0.7962 | 37 | |
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| 0.0148 | 0.9905 | 0.9947 | 1.8678 | 0.7868 | 0.7931 | 38 | |
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| 0.0117 | 0.9884 | 0.9968 | 1.7944 | 0.7868 | 0.7900 | 39 | |
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| 0.0137 | 0.9905 | 0.9958 | 1.7666 | 0.7900 | 0.7931 | 40 | |
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| 0.0160 | 0.9874 | 0.9958 | 1.7644 | 0.7868 | 0.7962 | 41 | |
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| 0.0150 | 0.9916 | 0.9937 | 1.7783 | 0.7868 | 0.8025 | 42 | |
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| 0.0128 | 0.9895 | 0.9958 | 1.7480 | 0.7900 | 0.7994 | 43 | |
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| 0.0102 | 0.9937 | 0.9947 | 1.7432 | 0.7931 | 0.7994 | 44 | |
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| 0.0138 | 0.9947 | 1.0 | 1.7511 | 0.7931 | 0.7994 | 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 |
