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arabert_baseline_relevance_task7_fold0

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  1. README.md +77 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
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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_baseline_relevance_task6_fold1
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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_task6_fold1
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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: 0.2487
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+ - Qwk: 0.4545
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+ - Mse: 0.2487
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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 | 0.5 | 2 | 0.2676 | 0.2727 | 0.2676 |
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+ | No log | 1.0 | 4 | 0.3056 | 0.2727 | 0.3056 |
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+ | No log | 1.5 | 6 | 0.2873 | 0.3636 | 0.2873 |
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+ | No log | 2.0 | 8 | 0.3326 | 0.3636 | 0.3326 |
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+ | No log | 2.5 | 10 | 0.2924 | 0.3636 | 0.2924 |
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+ | No log | 3.0 | 12 | 0.2560 | 0.3636 | 0.2560 |
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+ | No log | 3.5 | 14 | 0.2341 | 0.3636 | 0.2341 |
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+ | No log | 4.0 | 16 | 0.2402 | 0.4545 | 0.2402 |
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+ | No log | 4.5 | 18 | 0.2513 | 0.4545 | 0.2513 |
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+ | No log | 5.0 | 20 | 0.2596 | 0.4545 | 0.2596 |
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+ | No log | 5.5 | 22 | 0.2641 | 0.4545 | 0.2641 |
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+ | No log | 6.0 | 24 | 0.2500 | 0.4545 | 0.2500 |
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+ | No log | 6.5 | 26 | 0.2509 | 0.4545 | 0.2509 |
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+ | No log | 7.0 | 28 | 0.2495 | 0.4545 | 0.2495 |
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+ | No log | 7.5 | 30 | 0.2478 | 0.4545 | 0.2478 |
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+ | No log | 8.0 | 32 | 0.2467 | 0.4545 | 0.2467 |
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+ | No log | 8.5 | 34 | 0.2479 | 0.4545 | 0.2479 |
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+ | No log | 9.0 | 36 | 0.2484 | 0.4545 | 0.2484 |
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+ | No log | 9.5 | 38 | 0.2486 | 0.4545 | 0.2486 |
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+ | No log | 10.0 | 40 | 0.2487 | 0.4545 | 0.2487 |
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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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+ {
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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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+ "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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