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README.md

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+---
+license: apache-2.0
+base_model: sentence-transformers/all-MiniLM-L6-v2
+tags:
+- generated_from_keras_callback
+model-index:
+- name: kasrahabib/all-MiniLM-L6-v2-finetuned-iso29148-f_nf_req-embdr
+  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. -->
+
+# kasrahabib/all-MiniLM-L6-v2-finetuned-iso29148-f_nf_req-embdr
+
+This model is a fine-tuned version of [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Train Loss: 0.0009
+- Validation Loss: 0.6623
+- Epoch: 29
+
+## 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': 4710, '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 | Epoch |
+|:----------:|:---------------:|:-----:|
+| 0.5280     | 0.3710          | 0     |
+| 0.3075     | 0.3428          | 1     |
+| 0.2140     | 0.3139          | 2     |
+| 0.1252     | 0.3637          | 3     |
+| 0.0794     | 0.3695          | 4     |
+| 0.0506     | 0.4162          | 5     |
+| 0.0384     | 0.4577          | 6     |
+| 0.0253     | 0.4791          | 7     |
+| 0.0190     | 0.5735          | 8     |
+| 0.0119     | 0.5711          | 9     |
+| 0.0141     | 0.5977          | 10    |
+| 0.0131     | 0.5945          | 11    |
+| 0.0060     | 0.6052          | 12    |
+| 0.0098     | 0.6270          | 13    |
+| 0.0080     | 0.6484          | 14    |
+| 0.0098     | 0.6139          | 15    |
+| 0.0064     | 0.6103          | 16    |
+| 0.0067     | 0.6232          | 17    |
+| 0.0078     | 0.6205          | 18    |
+| 0.0067     | 0.6126          | 19    |
+| 0.0039     | 0.6108          | 20    |
+| 0.0039     | 0.6407          | 21    |
+| 0.0052     | 0.6501          | 22    |
+| 0.0043     | 0.6523          | 23    |
+| 0.0048     | 0.6800          | 24    |
+| 0.0071     | 0.6644          | 25    |
+| 0.0014     | 0.6600          | 26    |
+| 0.0026     | 0.6578          | 27    |
+| 0.0010     | 0.6613          | 28    |
+| 0.0009     | 0.6623          | 29    |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- TensorFlow 2.15.0
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "sentence-transformers/all-MiniLM-L6-v2",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "id2label": {
+    "0": "F",
+    "1": "NF"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "label2id": {
+    "F": 0,
+    "NF": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.40.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

logs/train/events.out.tfevents.1715693134.iste.1087584.0.v2

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logs/validation/events.out.tfevents.1715693175.iste.1087584.1.v2

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special_tokens_map.json

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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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+  "do_lower_case": true,
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+  "padding_side": "right",
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+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}