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arabert_cross_vocabulary_task4_fold5

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README.md ADDED
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+ ---
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+ base_model: aubmindlab/bert-base-arabertv02
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: arabert_cross_vocabulary_task4_fold4
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # arabert_cross_vocabulary_task4_fold4
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+
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+ This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6439
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+ - Qwk: 0.8180
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+ - Mse: 0.6439
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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+ |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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+ | No log | 0.0290 | 2 | 3.9935 | 0.0078 | 3.9935 |
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+ | No log | 0.0580 | 4 | 2.2937 | 0.0536 | 2.2937 |
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+ | No log | 0.0870 | 6 | 1.2377 | 0.1729 | 1.2377 |
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+ | No log | 0.1159 | 8 | 1.3353 | 0.1826 | 1.3353 |
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+ | No log | 0.1449 | 10 | 1.1216 | 0.4773 | 1.1216 |
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+ | No log | 0.1739 | 12 | 0.8392 | 0.5499 | 0.8392 |
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+ | No log | 0.2029 | 14 | 0.6966 | 0.6127 | 0.6966 |
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+ | No log | 0.2319 | 16 | 0.6473 | 0.6969 | 0.6473 |
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+ | No log | 0.2609 | 18 | 0.6961 | 0.7720 | 0.6961 |
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+ | No log | 0.2899 | 20 | 0.5180 | 0.8112 | 0.5180 |
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+ | No log | 0.3188 | 22 | 0.4069 | 0.7973 | 0.4069 |
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+ | No log | 0.3478 | 24 | 0.3749 | 0.7620 | 0.3749 |
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+ | No log | 0.3768 | 26 | 0.3945 | 0.7235 | 0.3945 |
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+ | No log | 0.4058 | 28 | 0.3796 | 0.7580 | 0.3796 |
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+ | No log | 0.4348 | 30 | 0.4995 | 0.8231 | 0.4995 |
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+ | No log | 0.4638 | 32 | 0.6489 | 0.7303 | 0.6489 |
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+ | No log | 0.4928 | 34 | 0.6807 | 0.6611 | 0.6807 |
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+ | No log | 0.5217 | 36 | 0.5950 | 0.7894 | 0.5950 |
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+ | No log | 0.5507 | 38 | 0.4549 | 0.8319 | 0.4549 |
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+ | No log | 0.5797 | 40 | 0.3601 | 0.7833 | 0.3601 |
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+ | No log | 0.6087 | 42 | 0.3472 | 0.7513 | 0.3472 |
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+ | No log | 0.6377 | 44 | 0.3541 | 0.716 | 0.3541 |
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+ | No log | 0.6667 | 46 | 0.3486 | 0.7411 | 0.3486 |
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+ | No log | 0.6957 | 48 | 0.3480 | 0.7678 | 0.3480 |
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+ | No log | 0.7246 | 50 | 0.3984 | 0.8135 | 0.3984 |
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+ | No log | 0.7536 | 52 | 0.5146 | 0.8349 | 0.5146 |
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+ | No log | 0.7826 | 54 | 0.6619 | 0.8250 | 0.6619 |
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+ | No log | 0.8116 | 56 | 0.7304 | 0.7951 | 0.7304 |
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+ | No log | 0.8406 | 58 | 0.7284 | 0.7985 | 0.7284 |
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+ | No log | 0.8696 | 60 | 0.7335 | 0.8019 | 0.7335 |
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+ | No log | 0.8986 | 62 | 0.7134 | 0.8053 | 0.7134 |
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+ | No log | 0.9275 | 64 | 0.6805 | 0.8133 | 0.6805 |
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+ | No log | 0.9565 | 66 | 0.6611 | 0.8180 | 0.6611 |
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+ | No log | 0.9855 | 68 | 0.6439 | 0.8180 | 0.6439 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.0
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+ - Pytorch 2.4.0
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
config.json ADDED
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+ {
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+ "_name_or_path": "aubmindlab/bert-base-arabertv02",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "LABEL_0"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "LABEL_0": 0
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "regression",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.44.0",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 64000
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+ }
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