End of training

README.md

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+---
+base_model: aubmindlab/bert-base-arabertv2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: medicalBert
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# medicalBert
+
+This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0432
+- Accuracy: 1.0
+
+## 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:
+- learning_rate: 2e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 19   | 1.3351          | 0.6579   |
+| No log        | 2.0   | 38   | 0.7920          | 0.8289   |
+| No log        | 3.0   | 57   | 0.4334          | 0.8684   |
+| No log        | 4.0   | 76   | 0.2400          | 0.9605   |
+| No log        | 5.0   | 95   | 0.1408          | 0.9868   |
+| No log        | 6.0   | 114  | 0.1014          | 1.0      |
+| No log        | 7.0   | 133  | 0.0681          | 1.0      |
+| No log        | 8.0   | 152  | 0.0478          | 1.0      |
+| No log        | 9.0   | 171  | 0.0442          | 1.0      |
+| No log        | 10.0  | 190  | 0.0432          | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "aubmindlab/bert-base-arabertv2",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Mental Health Disorders",
+    "1": "Cardiovascular Diseases",
+    "2": "Diabetes",
+    "3": "Cancer",
+    "4": "Respiratory Diseases"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Cancer": 3,
+    "Cardiovascular Diseases": 1,
+    "Diabetes": 2,
+    "Mental Health Disorders": 0,
+    "Respiratory Diseases": 4
+  },
+  "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",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.39.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 64000
+}

model.safetensors

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+size 540812300

runs/May26_23-54-48_7d03855d58c4/events.out.tfevents.1716767689.7d03855d58c4.84.0

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special_tokens_map.json

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+{
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+    "single_word": false
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+  "pad_token": {
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+    "lstrip": false,
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+    "rstrip": false,
+    "single_word": false
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+}

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