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arabert_cross_relevance_task1_fold2

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  1. README.md +88 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. runs/Sep01_12-24-37_39007f76a378/events.out.tfevents.1725193479.39007f76a378.36.0 +3 -0
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  9. runs/Sep01_12-33-11_39007f76a378/events.out.tfevents.1725194138.39007f76a378.36.5 +3 -0
  10. runs/Sep01_12-35-39_39007f76a378/events.out.tfevents.1725194140.39007f76a378.36.6 +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_cross_relevance_task1_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_cross_relevance_task1_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: 0.3646
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+ - Qwk: 0.0454
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+ - Mse: 0.3647
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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 | 0.0323 | 2 | 0.3884 | -0.0193 | 0.3901 |
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+ | No log | 0.0645 | 4 | 0.5676 | 0.0570 | 0.5677 |
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+ | No log | 0.0968 | 6 | 0.6160 | 0.1181 | 0.6161 |
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+ | No log | 0.1290 | 8 | 0.3914 | 0.0326 | 0.3913 |
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+ | No log | 0.1613 | 10 | 0.2970 | 0.0245 | 0.2972 |
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+ | No log | 0.1935 | 12 | 0.3016 | 0.0122 | 0.3018 |
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+ | No log | 0.2258 | 14 | 0.2905 | 0.0122 | 0.2908 |
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+ | No log | 0.2581 | 16 | 0.3013 | 0.0491 | 0.3016 |
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+ | No log | 0.2903 | 18 | 0.3427 | 0.0284 | 0.3429 |
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+ | No log | 0.3226 | 20 | 0.4170 | 0.0059 | 0.4170 |
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+ | No log | 0.3548 | 22 | 0.4971 | 0.0518 | 0.4971 |
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+ | No log | 0.3871 | 24 | 0.4934 | 0.0958 | 0.4933 |
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+ | No log | 0.4194 | 26 | 0.4203 | -0.0430 | 0.4203 |
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+ | No log | 0.4516 | 28 | 0.3668 | -0.0521 | 0.3669 |
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+ | No log | 0.4839 | 30 | 0.3462 | -0.0092 | 0.3463 |
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+ | No log | 0.5161 | 32 | 0.3500 | -0.0092 | 0.3500 |
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+ | No log | 0.5484 | 34 | 0.3623 | -0.0010 | 0.3623 |
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+ | No log | 0.5806 | 36 | 0.3911 | -0.0188 | 0.3911 |
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+ | No log | 0.6129 | 38 | 0.3635 | -0.0135 | 0.3634 |
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+ | No log | 0.6452 | 40 | 0.3500 | -0.0092 | 0.3500 |
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+ | No log | 0.6774 | 42 | 0.3369 | -0.0048 | 0.3369 |
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+ | No log | 0.7097 | 44 | 0.3357 | -0.0048 | 0.3358 |
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+ | No log | 0.7419 | 46 | 0.3574 | 0.0537 | 0.3574 |
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+ | No log | 0.7742 | 48 | 0.3901 | 0.0370 | 0.3901 |
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+ | No log | 0.8065 | 50 | 0.3986 | 0.0723 | 0.3985 |
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+ | No log | 0.8387 | 52 | 0.3875 | 0.0544 | 0.3875 |
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+ | No log | 0.8710 | 54 | 0.3792 | 0.0586 | 0.3792 |
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+ | No log | 0.9032 | 56 | 0.3727 | 0.0412 | 0.3727 |
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+ | No log | 0.9355 | 58 | 0.3667 | 0.0454 | 0.3667 |
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+ | No log | 0.9677 | 60 | 0.3648 | 0.0454 | 0.3648 |
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+ | No log | 1.0 | 62 | 0.3646 | 0.0454 | 0.3647 |
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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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+ "hidden_act": "gelu",
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+ "id2label": {
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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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