Training in progress epoch 0

README.md

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+---
+license: apache-2.0
+base_model: albert-base-v2
+tags:
+- generated_from_keras_callback
+model-index:
+- name: Kemasu/albert-base-v2-finetuned-squad
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information Keras had access to. You should
+probably proofread and complete it, then remove this comment. -->
+
+# Kemasu/albert-base-v2-finetuned-squad
+
+This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Train Loss: 1.0013
+- Train End Logits Accuracy: 0.7316
+- Train Start Logits Accuracy: 0.6900
+- Validation Loss: 0.8895
+- Validation End Logits Accuracy: 0.7531
+- Validation Start Logits Accuracy: 0.7122
+- Epoch: 0
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- 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}
+- training_precision: float32
+
+### Training results
+
+| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
+|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
+| 1.0013     | 0.7316                    | 0.6900                      | 0.8895          | 0.7531                         | 0.7122                           | 0     |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- TensorFlow 2.15.0
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "albert-base-v2",
+  "architectures": [
+    "AlbertForQuestionAnswering"
+  ],
+  "attention_probs_dropout_prob": 0,
+  "bos_token_id": 2,
+  "classifier_dropout_prob": 0.1,
+  "down_scale_factor": 1,
+  "embedding_size": 128,
+  "eos_token_id": 3,
+  "gap_size": 0,
+  "hidden_act": "gelu_new",
+  "hidden_dropout_prob": 0,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "inner_group_num": 1,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "albert",
+  "net_structure_type": 0,
+  "num_attention_heads": 12,
+  "num_hidden_groups": 1,
+  "num_hidden_layers": 12,
+  "num_memory_blocks": 0,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.38.2",
+  "type_vocab_size": 2,
+  "vocab_size": 30000
+}

logs/train/events.out.tfevents.1710966306.66e0f31e12df.796.0.v2

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logs/validation/events.out.tfevents.1710973052.66e0f31e12df.796.1.v2

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special_tokens_map.json

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+  "sep_token": "[SEP]",
+  "unk_token": "<unk>"
+}

spiece.model

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tf_model.h5

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tokenizer_config.json

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+{
+  "added_tokens_decoder": {
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+      "normalized": false,
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+      "single_word": false,
+      "special": true
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+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
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+  "eos_token": "[SEP]",
+  "keep_accents": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
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+  "tokenizer_class": "AlbertTokenizer",
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+}