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--- |
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license: mit |
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base_model: xlm-roberta-base |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: vnktrmnb/xlm-roberta-base-FT-TyDiQA_AUQC |
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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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# vnktrmnb/xlm-roberta-base-FT-TyDiQA_AUQC |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.7421 |
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- Train End Logits Accuracy: 0.8018 |
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- Train Start Logits Accuracy: 0.8399 |
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- Validation Loss: 0.4881 |
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- Validation End Logits Accuracy: 0.8434 |
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- Validation Start Logits Accuracy: 0.8909 |
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- Epoch: 2 |
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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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 4176, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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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| 1.7701 | 0.5788 | 0.6180 | 0.5240 | 0.8406 | 0.8811 | 0 | |
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| 0.9970 | 0.7439 | 0.7841 | 0.4812 | 0.8434 | 0.8979 | 1 | |
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| 0.7421 | 0.8018 | 0.8399 | 0.4881 | 0.8434 | 0.8909 | 2 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- TensorFlow 2.12.0 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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