End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: intfloat/e5-small
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: intfloat-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-e5-small-arabic-fp16
+
+This model is a fine-tuned version of [intfloat/e5-small](https://huggingface.co/intfloat/e5-small) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7833
+- Accuracy: 0.6782
+- Precision: 0.6650
+- Recall: 0.6782
+- F1: 0.6560
+
+## 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     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 1.0984        | 0.3636 | 50   | 1.0847          | 0.4373   | 0.5309    | 0.4373 | 0.2662 |
+| 1.069         | 0.7273 | 100  | 1.0270          | 0.5677   | 0.6816    | 0.5677 | 0.4864 |
+| 1.0003        | 1.0873 | 150  | 0.9488          | 0.6041   | 0.6923    | 0.6041 | 0.5281 |
+| 0.9438        | 1.4509 | 200  | 0.9085          | 0.6095   | 0.7017    | 0.6095 | 0.5340 |
+| 0.9178        | 1.8145 | 250  | 0.9204          | 0.5895   | 0.6283    | 0.5895 | 0.5182 |
+| 0.8936        | 2.1745 | 300  | 0.8394          | 0.6441   | 0.5970    | 0.6441 | 0.5653 |
+| 0.8824        | 2.5382 | 350  | 0.8447          | 0.6464   | 0.7275    | 0.6464 | 0.5674 |
+| 0.8774        | 2.9018 | 400  | 0.8706          | 0.625    | 0.6165    | 0.625  | 0.5859 |
+| 0.8655        | 3.2618 | 450  | 0.8125          | 0.6541   | 0.6337    | 0.6541 | 0.6378 |
+| 0.8517        | 3.6255 | 500  | 0.8528          | 0.6477   | 0.6565    | 0.6477 | 0.6013 |
+| 0.8451        | 3.9891 | 550  | 0.7914          | 0.6686   | 0.6502    | 0.6686 | 0.6340 |
+| 0.8084        | 4.3491 | 600  | 0.7833          | 0.6782   | 0.6650    | 0.6782 | 0.6560 |
+| 0.8028        | 4.7127 | 650  | 0.7635          | 0.6923   | 0.6832    | 0.6923 | 0.6803 |
+| 0.7874        | 5.0727 | 700  | 0.7815          | 0.6709   | 0.6828    | 0.6709 | 0.6754 |
+| 0.7861        | 5.4364 | 750  | 0.7629          | 0.6873   | 0.6811    | 0.6873 | 0.6820 |
+| 0.7593        | 5.8    | 800  | 0.7794          | 0.6823   | 0.6744    | 0.6823 | 0.6684 |
+| 0.753         | 6.16   | 850  | 0.7680          | 0.6845   | 0.6859    | 0.6845 | 0.6838 |
+| 0.753         | 6.5236 | 900  | 0.8404          | 0.6395   | 0.6783    | 0.6395 | 0.6459 |
+
+
+### 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",
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

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training_args.bin

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