Upload TFBertForSequenceClassification

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_keras_callback
+model-index:
+- name: vc-01-bert-finetuned
+  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. -->
+
+# vc-01-bert-finetuned
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Train Loss: 0.0074
+- Validation Loss: 0.4494
+- Train Recall: 0.9247
+- Epoch: 8
+
+## 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': 7920, '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 | Validation Loss | Train Recall | Epoch |
+|:----------:|:---------------:|:------------:|:-----:|
+| 0.3152     | 0.3003          | 0.9383       | 0     |
+| 0.1993     | 0.2504          | 0.9036       | 1     |
+| 0.1250     | 0.2717          | 0.9232       | 2     |
+| 0.0654     | 0.3074          | 0.8870       | 3     |
+| 0.0347     | 0.3127          | 0.9232       | 4     |
+| 0.0268     | 0.4317          | 0.9217       | 5     |
+| 0.0146     | 0.4449          | 0.9066       | 6     |
+| 0.0092     | 0.4419          | 0.9066       | 7     |
+| 0.0074     | 0.4494          | 0.9247       | 8     |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- TensorFlow 2.13.0
+- Datasets 2.14.4
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "bert-base-uncased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "0",
+    "1": "1"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "0": 0,
+    "1": 1
+  },
+  "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": "4.31.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

tf_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:17ec2db81c7b396708ae270ccf6cc67f38965fc0100c7c9576077313ce8e115e
+size 438223128