End of training

README.md

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+---
+base_model: aubmindlab/bert-base-arabertv2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: arabertv2-fully-supervised-arabic-propaganda
+  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. -->
+
+# arabertv2-fully-supervised-arabic-propaganda
+
+This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3894
+- Accuracy: 0.9262
+- Precision: 0.6042
+- Recall: 0.7073
+- F1: 0.6517
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.4919        | 1.0   | 20   | 0.5087          | 0.8381   | 0.3516    | 0.7805 | 0.4848 |
+| 0.3633        | 2.0   | 40   | 0.4010          | 0.8333   | 0.3474    | 0.8049 | 0.4853 |
+| 0.2017        | 3.0   | 60   | 0.3635          | 0.9      | 0.4918    | 0.7317 | 0.5882 |
+| 0.3071        | 4.0   | 80   | 0.3981          | 0.9333   | 0.6444    | 0.7073 | 0.6744 |
+| 0.145         | 5.0   | 100  | 0.3894          | 0.9262   | 0.6042    | 0.7073 | 0.6517 |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu121
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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": "Transparent",
+    "1": "Propaganda"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Propaganda": 1,
+    "Transparent": 0
+  },
+  "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",
+  "torch_dtype": "float32",
+  "transformers_version": "4.35.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 64000
+}

model.safetensors

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runs/Nov14_11-32-28_nl6hirvnmq/events.out.tfevents.1699961575.nl6hirvnmq.451.0

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runs/Nov14_11-32-28_nl6hirvnmq/events.out.tfevents.1699961657.nl6hirvnmq.451.1

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special_tokens_map.json

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+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+  "tokenizer_class": "BertTokenizer",
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+}

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