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  1. .gitattributes +35 -0
  2. README.md +59 -0
  3. config.json +32 -0
  4. special_tokens_map.json +15 -0
  5. spiece.model +3 -0
  6. tf_model.h5 +3 -0
  7. tokenizer.json +0 -0
  8. tokenizer_config.json +57 -0
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: albert-base-v2
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+ tags:
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+ - generated_from_keras_callback
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+ model-index:
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+ - name: Kemasu/albert-base-v2-finetuned-squad
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+ results: []
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+ ---
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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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+
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+ # Kemasu/albert-base-v2-finetuned-squad
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+
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+ This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Train Loss: 0.6529
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+ - Train End Logits Accuracy: 0.8116
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+ - Train Start Logits Accuracy: 0.7711
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+ - Validation Loss: 0.8559
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+ - Validation End Logits Accuracy: 0.7604
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+ - Validation Start Logits Accuracy: 0.7262
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+ - Epoch: 1
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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': 2e-05, 'decay_steps': 11078, '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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+
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+ ### Training results
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+
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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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+ | 0.9838 | 0.7333 | 0.6924 | 0.8735 | 0.7515 | 0.7178 | 0 |
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+ | 0.6529 | 0.8116 | 0.7711 | 0.8559 | 0.7604 | 0.7262 | 1 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - TensorFlow 2.15.0
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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+ ],
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "albert",
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+ "net_structure_type": 0,
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+ "type_vocab_size": 2,
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+ "vocab_size": 30000
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+ }
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