End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: intfloat/e5-large-v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: intfloat-e5-large-v2-arabic-fp16
+  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. -->
+
+# intfloat-e5-large-v2-arabic-fp16
+
+This model is a fine-tuned version of [intfloat/e5-large-v2](https://huggingface.co/intfloat/e5-large-v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6592
+- Accuracy: 0.7391
+- Precision: 0.7362
+- Recall: 0.7391
+- F1: 0.7359
+
+## 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
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 128
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.3
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 1.0807        | 0.3636 | 50   | 0.9715          | 0.5777   | 0.7072    | 0.5777 | 0.4953 |
+| 0.8958        | 0.7273 | 100  | 0.7766          | 0.6836   | 0.6848    | 0.6836 | 0.6548 |
+| 0.8091        | 1.0873 | 150  | 0.7413          | 0.6959   | 0.6882    | 0.6959 | 0.6763 |
+| 0.76          | 1.4509 | 200  | 0.7037          | 0.7177   | 0.7123    | 0.7177 | 0.7075 |
+| 0.7426        | 1.8145 | 250  | 0.7449          | 0.6959   | 0.6974    | 0.6959 | 0.6900 |
+| 0.7371        | 2.1745 | 300  | 0.7117          | 0.6968   | 0.6983    | 0.6968 | 0.6949 |
+| 0.7083        | 2.5382 | 350  | 0.6896          | 0.715    | 0.7152    | 0.715  | 0.7150 |
+| 0.6937        | 2.9018 | 400  | 0.6967          | 0.7259   | 0.7289    | 0.7259 | 0.7083 |
+| 0.6792        | 3.2618 | 450  | 0.6680          | 0.7341   | 0.7363    | 0.7341 | 0.7238 |
+| 0.6646        | 3.6255 | 500  | 0.7275          | 0.69     | 0.7101    | 0.69   | 0.6945 |
+| 0.6654        | 3.9891 | 550  | 0.6666          | 0.7309   | 0.7315    | 0.7309 | 0.7212 |
+| 0.6065        | 4.3491 | 600  | 0.6592          | 0.7391   | 0.7362    | 0.7391 | 0.7359 |
+| 0.6112        | 4.7127 | 650  | 0.6468          | 0.7395   | 0.7392    | 0.7395 | 0.7392 |
+| 0.592         | 5.0727 | 700  | 0.6657          | 0.7336   | 0.7324    | 0.7336 | 0.7317 |
+| 0.5624        | 5.4364 | 750  | 0.6740          | 0.73     | 0.7404    | 0.73   | 0.7306 |
+| 0.5333        | 5.8    | 800  | 0.6732          | 0.7423   | 0.7397    | 0.7423 | 0.7404 |
+
+
+### Framework versions
+
+- Transformers 4.51.1
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.21.1

config.json

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+{
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "negative",
+    "1": "positive",
+    "2": "neutral"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "negative": 0,
+    "neutral": 2,
+    "positive": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

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