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Model save

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  1. README.md +13 -13
  2. config.json +8 -8
README.md CHANGED
@@ -1,5 +1,5 @@
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  ---
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- base_model: aubmindlab/bert-large-arabertv02-twitter
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -14,11 +14,11 @@ should probably proofread and complete it, then remove this comment. -->
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  # arabert-sentiment-classification
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- This model is a fine-tuned version of [aubmindlab/bert-large-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-large-arabertv02-twitter) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5525
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- - Macro F1: 0.6558
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- - Accuracy: 0.7957
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  ## Model description
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@@ -38,11 +38,11 @@ More information needed
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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: 128
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- - seed: 25
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  - gradient_accumulation_steps: 2
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- - total_train_batch_size: 32
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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: 2
@@ -51,12 +51,12 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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- | No log | 1.0 | 497 | 0.5462 | 0.6431 | 0.7925 |
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- | 0.6202 | 2.0 | 994 | 0.5525 | 0.6558 | 0.7957 |
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  ### Framework versions
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- - Transformers 4.33.3
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- - Pytorch 2.0.1+cu118
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- - Tokenizers 0.13.3
 
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  ---
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+ base_model: aubmindlab/bert-large-arabertv02
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # arabert-sentiment-classification
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+ This model is a fine-tuned version of [aubmindlab/bert-large-arabertv02](https://huggingface.co/aubmindlab/bert-large-arabertv02) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7645
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+ - Macro F1: 0.7216
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+ - Accuracy: 0.7216
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  ## Model description
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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: 32
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  - eval_batch_size: 128
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+ - seed: 42
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  - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 64
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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: 2
 
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  | Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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+ | No log | 1.0 | 249 | 1.0181 | 0.5867 | 0.5867 |
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+ | No log | 2.0 | 498 | 0.7645 | 0.7216 | 0.7216 |
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  ### Framework versions
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+ - Transformers 4.34.0
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+ - Pytorch 1.12.0
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+ - Tokenizers 0.14.1
config.json CHANGED
@@ -9,18 +9,18 @@
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  "hidden_dropout_prob": 0.1,
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  "hidden_size": 1024,
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  "id2label": {
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- "0": "LABEL_0",
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- "1": "LABEL_1",
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- "2": "LABEL_2",
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- "3": "LABEL_3"
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  },
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  "initializer_range": 0.02,
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  "intermediate_size": 4096,
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  "label2id": {
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- "LABEL_0": 0,
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- "LABEL_1": 1,
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- "LABEL_2": 2,
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- "LABEL_3": 3
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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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  "hidden_dropout_prob": 0.1,
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  "hidden_size": 1024,
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  "id2label": {
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+ "0": "Positive",
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+ "1": "Negative",
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+ "2": "Neutral",
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+ "3": "Mixed"
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  },
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  "initializer_range": 0.02,
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  "intermediate_size": 4096,
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  "label2id": {
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+ "Mixed": 3,
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+ "Negative": 1,
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+ "Neutral": 2,
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+ "Positive": 0
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  },
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  "layer_norm_eps": 1e-12,
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  "max_position_embeddings": 512,