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--- |
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license: apache-2.0 |
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base_model: PlanTL-GOB-ES/roberta-base-bne |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: lulygavri/rob-conv |
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results: [] |
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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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# lulygavri/rob-conv |
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This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0787 |
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- Validation Loss: 0.0220 |
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- Train Accuracy: 0.9948 |
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- Train Precision: [0.95822589 0.99925584 0.99829758] |
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- Train Precision W: 0.9949 |
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- Train Recall: [0.99678112 0.99385686 0.99761824] |
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- Train Recall W: 0.9948 |
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- Train F1: [0.97712332 0.99654904 0.99795779] |
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- Train F1 W: 0.9948 |
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- Epoch: 1 |
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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': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3964, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 500, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False} |
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- training_precision: mixed_float16 |
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### Training results |
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| Train Loss | Validation Loss | Train Accuracy | Train Precision | Train Precision W | Train Recall | Train Recall W | Train F1 | Train F1 W | Epoch | |
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|:----------:|:---------------:|:--------------:|:----------------------------------:|:-----------------:|:----------------------------------:|:--------------:|:----------------------------------:|:----------:|:-----:| |
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| 0.0787 | 0.0220 | 0.9948 | [0.95822589 0.99925584 0.99829758] | 0.9949 | [0.99678112 0.99385686 0.99761824] | 0.9948 | [0.97712332 0.99654904 0.99795779] | 0.9948 | 1 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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