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arabert_baseline_relevance_task5_fold1

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  1. README.md +87 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. runs/Aug27_16-09-30_353807a3cce0/events.out.tfevents.1724774972.353807a3cce0.22.0 +3 -0
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  13. runs/Aug27_16-20-50_353807a3cce0/events.out.tfevents.1724775652.353807a3cce0.22.9 +3 -0
  14. training_args.bin +3 -0
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_baseline_relevance_task5_fold0
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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_baseline_relevance_task5_fold0
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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: 0.3678
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+ - Qwk: 0.2949
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+ - Mse: 0.3678
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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: 10
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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 | 0.3333 | 2 | 0.4684 | 0.1304 | 0.4684 |
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+ | No log | 0.6667 | 4 | 0.4252 | 0.0 | 0.4252 |
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+ | No log | 1.0 | 6 | 0.4179 | 0.0 | 0.4179 |
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+ | No log | 1.3333 | 8 | 0.4231 | 0.0 | 0.4231 |
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+ | No log | 1.6667 | 10 | 0.4130 | 0.0 | 0.4130 |
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+ | No log | 2.0 | 12 | 0.4098 | 0.0 | 0.4098 |
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+ | No log | 2.3333 | 14 | 0.4153 | 0.0551 | 0.4153 |
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+ | No log | 2.6667 | 16 | 0.4026 | 0.0551 | 0.4026 |
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+ | No log | 3.0 | 18 | 0.3622 | 0.1837 | 0.3622 |
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+ | No log | 3.3333 | 20 | 0.3561 | 0.1837 | 0.3561 |
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+ | No log | 3.6667 | 22 | 0.3628 | 0.1837 | 0.3628 |
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+ | No log | 4.0 | 24 | 0.3773 | 0.1837 | 0.3773 |
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+ | No log | 4.3333 | 26 | 0.3744 | 0.1837 | 0.3744 |
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+ | No log | 4.6667 | 28 | 0.3673 | 0.1837 | 0.3673 |
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+ | No log | 5.0 | 30 | 0.3744 | 0.1837 | 0.3744 |
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+ | No log | 5.3333 | 32 | 0.3730 | 0.1837 | 0.3730 |
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+ | No log | 5.6667 | 34 | 0.3589 | 0.1333 | 0.3589 |
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+ | No log | 6.0 | 36 | 0.3503 | 0.3464 | 0.3503 |
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+ | No log | 6.3333 | 38 | 0.3556 | 0.2949 | 0.3556 |
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+ | No log | 6.6667 | 40 | 0.3713 | 0.2949 | 0.3713 |
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+ | No log | 7.0 | 42 | 0.3743 | 0.2949 | 0.3743 |
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+ | No log | 7.3333 | 44 | 0.3742 | 0.2949 | 0.3742 |
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+ | No log | 7.6667 | 46 | 0.3719 | 0.2949 | 0.3719 |
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+ | No log | 8.0 | 48 | 0.3699 | 0.2949 | 0.3699 |
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+ | No log | 8.3333 | 50 | 0.3712 | 0.2949 | 0.3712 |
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+ | No log | 8.6667 | 52 | 0.3661 | 0.2949 | 0.3661 |
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+ | No log | 9.0 | 54 | 0.3649 | 0.2157 | 0.3649 |
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+ | No log | 9.3333 | 56 | 0.3664 | 0.1333 | 0.3664 |
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+ | No log | 9.6667 | 58 | 0.3674 | 0.2157 | 0.3674 |
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+ | No log | 10.0 | 60 | 0.3678 | 0.2949 | 0.3678 |
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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
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+ "BertForSequenceClassification"
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+ "initializer_range": 0.02,
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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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