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Model4_arabertv2_base_T2_WS_A100

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
text-embeddings-inference
Model card Files
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update model card README.md

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@@ -17,10 +17,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-base-arabertv02-twitter) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0654
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- - F1: 0.8501
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- - Roc Auc: 0.9178
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- - Accuracy: 0.7616
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  ## Model description
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@@ -51,15 +51,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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- | No log | 1.0 | 193 | 0.1020 | 0.7502 | 0.8274 | 0.6443 |
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- | No log | 2.0 | 386 | 0.0759 | 0.8068 | 0.8678 | 0.7114 |
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- | 0.1069 | 3.0 | 579 | 0.0728 | 0.8240 | 0.8890 | 0.7393 |
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- | 0.1069 | 4.0 | 772 | 0.0670 | 0.8418 | 0.9112 | 0.7635 |
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- | 0.1069 | 5.0 | 965 | 0.0654 | 0.8501 | 0.9178 | 0.7616 |
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- | 0.0318 | 6.0 | 1158 | 0.0669 | 0.8467 | 0.9197 | 0.7579 |
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- | 0.0318 | 7.0 | 1351 | 0.0686 | 0.8471 | 0.9190 | 0.7672 |
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- | 0.0141 | 8.0 | 1544 | 0.0705 | 0.8493 | 0.9259 | 0.7561 |
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- | 0.0141 | 9.0 | 1737 | 0.0732 | 0.8450 | 0.9248 | 0.7486 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-base-arabertv02-twitter) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0694
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+ - F1: 0.8430
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+ - Roc Auc: 0.9128
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+ - Accuracy: 0.7523
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | No log | 1.0 | 193 | 0.0694 | 0.8430 | 0.9128 | 0.7523 |
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+ | No log | 2.0 | 386 | 0.0713 | 0.8489 | 0.9184 | 0.7598 |
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+ | 0.0183 | 3.0 | 579 | 0.0779 | 0.8377 | 0.9226 | 0.7412 |
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+ | 0.0183 | 4.0 | 772 | 0.0727 | 0.8455 | 0.9181 | 0.7523 |
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+ | 0.0183 | 5.0 | 965 | 0.0749 | 0.8555 | 0.9264 | 0.7672 |
 
 
 
 
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  ### Framework versions