End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: intfloat/multilingual-e5-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: intfloat-multilingual-e5-large-arabic-fp16-allagree
+  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-multilingual-e5-large-arabic-fp16-allagree
+
+This model is a fine-tuned version of [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1942
+- Accuracy: 0.9347
+- Precision: 0.9349
+- Recall: 0.9347
+- F1: 0.9346
+
+## 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     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.9731        | 0.7463 | 50   | 0.6211          | 0.7603   | 0.8128    | 0.7603 | 0.6907 |
+| 0.375         | 1.4925 | 100  | 0.1942          | 0.9347   | 0.9349    | 0.9347 | 0.9346 |
+| 0.1713        | 2.2388 | 150  | 0.1802          | 0.9412   | 0.9414    | 0.9412 | 0.9412 |
+| 0.1466        | 2.9851 | 200  | 0.2002          | 0.9291   | 0.9303    | 0.9291 | 0.9287 |
+| 0.0936        | 3.7313 | 250  | 0.2041          | 0.9356   | 0.9356    | 0.9356 | 0.9356 |
+| 0.0577        | 4.4776 | 300  | 0.2556          | 0.9431   | 0.9436    | 0.9431 | 0.9432 |
+
+
+### 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": [
+    "XLMRobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "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-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

model.safetensors

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runs/Apr15_12-24-26_1ce9172a2a99/events.out.tfevents.1744719885.1ce9172a2a99.1097.4

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training_args.bin

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