Upload TFBertForSequenceClassification

README.md

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+---
+library_name: transformers
+license: cc-by-sa-4.0
+base_model: klue/bert-base
+tags:
+- generated_from_keras_callback
+model-index:
+- name: bert-base-nsmc
+  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. -->
+
+# bert-base-nsmc
+
+This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Train Loss: 0.0288
+- Train Accuracy: 0.9914
+- Validation Loss: 0.5336
+- Validation Accuracy: 0.8714
+- Epoch: 4
+
+## 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': 'AdamWeightDecay', 'learning_rate': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 5e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 1058, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 117, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': np.float32(0.9), 'beta_2': np.float32(0.999), 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.1}
+- training_precision: float32
+
+### Training results
+
+| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
+|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
+| 0.3967     | 0.8134         | 0.3805          | 0.8266              | 0     |
+| 0.2183     | 0.9149         | 0.3068          | 0.8740              | 1     |
+| 0.1075     | 0.9622         | 0.4280          | 0.8696              | 2     |
+| 0.0481     | 0.9843         | 0.4970          | 0.8722              | 3     |
+| 0.0288     | 0.9914         | 0.5336          | 0.8714              | 4     |
+
+
+### Framework versions
+
+- Transformers 4.55.2
+- TensorFlow 2.19.0
+- Datasets 4.0.0
+- Tokenizers 0.21.4

config.json

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+{
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "\ubd80\uc815",
+    "1": "\uae0d\uc815"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.55.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 32000
+}

tf_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d6eb337f0a7ced0ad048f1e3ac44d99bd9bde40a8069ce9b8db735613895fd84
+size 442763544