End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: intfloat/multilingual-e5-small
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: intfloat-multilingual-e5-small-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-multilingual-e5-small-arabic-fp16
+
+This model is a fine-tuned version of [intfloat/multilingual-e5-small](https://huggingface.co/intfloat/multilingual-e5-small) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5545
+- Accuracy: 0.7845
+- Precision: 0.7877
+- Recall: 0.7845
+- F1: 0.7855
+
+## 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     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 1.1004        | 0.3636 | 50   | 1.0937          | 0.4409   | 0.5501    | 0.4409 | 0.2840 |
+| 1.0836        | 0.7273 | 100  | 1.0569          | 0.4923   | 0.7472    | 0.4923 | 0.3721 |
+| 1.0058        | 1.0873 | 150  | 0.9185          | 0.6682   | 0.7418    | 0.6682 | 0.5839 |
+| 0.8875        | 1.4509 | 200  | 0.8000          | 0.7191   | 0.7297    | 0.7191 | 0.6883 |
+| 0.7929        | 1.8145 | 250  | 0.7344          | 0.7436   | 0.7441    | 0.7436 | 0.7432 |
+| 0.7229        | 2.1745 | 300  | 0.6749          | 0.7573   | 0.7585    | 0.7573 | 0.7575 |
+| 0.6733        | 2.5382 | 350  | 0.6474          | 0.7677   | 0.7692    | 0.7677 | 0.7613 |
+| 0.6496        | 2.9018 | 400  | 0.6064          | 0.7805   | 0.7852    | 0.7805 | 0.7803 |
+| 0.5981        | 3.2618 | 450  | 0.5917          | 0.7782   | 0.7835    | 0.7782 | 0.7779 |
+| 0.5646        | 3.6255 | 500  | 0.5961          | 0.7755   | 0.7812    | 0.7755 | 0.7773 |
+| 0.5663        | 3.9891 | 550  | 0.5629          | 0.7891   | 0.7880    | 0.7891 | 0.7884 |
+| 0.5179        | 4.3491 | 600  | 0.5673          | 0.7905   | 0.7900    | 0.7905 | 0.7880 |
+| 0.5167        | 4.7127 | 650  | 0.5993          | 0.7618   | 0.7787    | 0.7618 | 0.7657 |
+| 0.4984        | 5.0727 | 700  | 0.5545          | 0.7845   | 0.7877    | 0.7845 | 0.7855 |
+| 0.4905        | 5.4364 | 750  | 0.5496          | 0.7936   | 0.7926    | 0.7936 | 0.7926 |
+| 0.474         | 5.8    | 800  | 0.5585          | 0.7832   | 0.7842    | 0.7832 | 0.7836 |
+| 0.457         | 6.16   | 850  | 0.5726          | 0.785    | 0.7876    | 0.785  | 0.7860 |
+| 0.4471        | 6.5236 | 900  | 0.5530          | 0.7886   | 0.7873    | 0.7886 | 0.7877 |
+
+
+### 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": 384,
+  "id2label": {
+    "0": "negative",
+    "1": "positive",
+    "2": "neutral"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "label2id": {
+    "negative": 0,
+    "neutral": 2,
+    "positive": 1
+  },
+  "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",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 250037
+}

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training_args.bin

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