Upload TFDistilBertForSequenceClassification

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_keras_callback
+model-index:
+- name: ac-01-distilbert-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. -->
+
+# ac-01-distilbert-finetuned
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Train Loss: 0.0135
+- Validation Loss: 0.5022
+- Train Recall: 0.8636
+- 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': 1500, '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 |
+|:----------:|:---------------:|:------------:|:-----:|
+| 0.5302     | 0.2915          | 0.9167       | 0     |
+| 0.2481     | 0.2611          | 0.8788       | 1     |
+| 0.1306     | 0.2634          | 0.9167       | 2     |
+| 0.0701     | 0.3197          | 0.8636       | 3     |
+| 0.0352     | 0.3511          | 0.8864       | 4     |
+| 0.0199     | 0.3923          | 0.9091       | 5     |
+| 0.0168     | 0.4305          | 0.8864       | 6     |
+| 0.0140     | 0.4629          | 0.8788       | 7     |
+| 0.0135     | 0.5022          | 0.8636       | 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": "distilbert-base-uncased",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "0",
+    "1": "1"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "0": 0,
+    "1": 1
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "transformers_version": "4.31.0",
+  "vocab_size": 30522
+}

tf_model.h5

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+oid sha256:eb89c80c5672b4776a80a2c0c5ea527559c92177a9002471ca9aa04c81e1f854
+size 267955144