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thejosango
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nuha-ajp-binary

Text Classification
Transformers
PyTorch
Safetensors
Arabic
bert
hate-speech
gender-based-violence
arabic
binary-classification
pilot
Eval Results (legacy)
text-embeddings-inference
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yazansh commited on
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binary-29

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Files changed (4) hide show
  1. README.md +19 -23
  2. config.toml +3 -3
  3. pytorch_model.bin +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -23,13 +23,13 @@ model-index:
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  metrics:
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  - name: F1
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  type: f1
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- value: 0.6658038273088657
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  - name: Precision
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  type: precision
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- value: 0.6663582531458179
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  - name: Recall
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  type: recall
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- value: 0.6652503232957695
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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
@@ -39,10 +39,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [thejosango/nuha-mlm](https://huggingface.co/thejosango/nuha-mlm) on the nuha-dataset dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5203
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- - F1: 0.6658
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- - Precision: 0.6664
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- - Recall: 0.6653
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  - Support: None
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  ## Model description
@@ -78,22 +78,18 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Support |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:-------:|
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- | 1.0669 | 0.09 | 500 | 1.0365 | 0.5699 | 0.4064 | 0.9531 | None |
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- | 0.8978 | 0.18 | 1000 | 1.1794 | 0.5709 | 0.4036 | 0.9756 | None |
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- | 0.8142 | 0.28 | 1500 | 0.5742 | 0.6380 | 0.5748 | 0.7168 | None |
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- | 0.7269 | 0.37 | 2000 | 0.5638 | 0.6455 | 0.6096 | 0.6858 | None |
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- | 0.7215 | 0.46 | 2500 | 0.5475 | 0.6454 | 0.6287 | 0.6630 | None |
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- | 0.6828 | 0.55 | 3000 | 0.5702 | 0.6528 | 0.5803 | 0.7460 | None |
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- | 0.6857 | 0.65 | 3500 | 0.5348 | 0.6081 | 0.6636 | 0.5612 | None |
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- | 0.6381 | 0.74 | 4000 | 0.5609 | 0.6654 | 0.5913 | 0.7608 | None |
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- | 0.6476 | 0.83 | 4500 | 0.5565 | 0.6662 | 0.5972 | 0.7532 | None |
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- | 0.6124 | 0.92 | 5000 | 0.5468 | 0.6662 | 0.6114 | 0.7318 | None |
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- | 0.6292 | 1.02 | 5500 | 0.5409 | 0.6737 | 0.6217 | 0.7353 | None |
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- | 0.5904 | 1.11 | 6000 | 0.5565 | 0.6736 | 0.6036 | 0.7621 | None |
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- | 0.5926 | 1.2 | 6500 | 0.6091 | 0.6668 | 0.5439 | 0.8614 | None |
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- | 0.5962 | 1.29 | 7000 | 0.6201 | 0.6650 | 0.5368 | 0.8736 | None |
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- | 0.6056 | 1.39 | 7500 | 0.5477 | 0.6775 | 0.5975 | 0.7824 | None |
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- | 0.582 | 1.48 | 8000 | 0.5203 | 0.6658 | 0.6664 | 0.6653 | None |
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  ### Framework versions
 
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  metrics:
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  - name: F1
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  type: f1
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+ value: 0.6823729337247026
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  - name: Precision
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  type: precision
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+ value: 0.5863533784680738
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  - name: Recall
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  type: recall
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+ value: 0.8159985220764825
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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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  This model is a fine-tuned version of [thejosango/nuha-mlm](https://huggingface.co/thejosango/nuha-mlm) on the nuha-dataset dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5626
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+ - F1: 0.6824
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+ - Precision: 0.5864
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+ - Recall: 0.8160
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  - Support: None
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  ## Model description
 
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Support |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:-------:|
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+ | 0.6128 | 0.09 | 500 | 0.5843 | 0.6389 | 0.5519 | 0.7585 | None |
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+ | 0.5868 | 0.18 | 1000 | 0.5623 | 0.6458 | 0.5706 | 0.7438 | None |
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+ | 0.5746 | 0.28 | 1500 | 0.5489 | 0.6557 | 0.5971 | 0.7270 | None |
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+ | 0.5718 | 0.37 | 2000 | 0.5487 | 0.6640 | 0.5997 | 0.7438 | None |
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+ | 0.5727 | 0.46 | 2500 | 0.5417 | 0.6627 | 0.6166 | 0.7162 | None |
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+ | 0.5532 | 0.55 | 3000 | 0.5525 | 0.6683 | 0.5842 | 0.7807 | None |
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+ | 0.5552 | 0.65 | 3500 | 0.5337 | 0.6752 | 0.6266 | 0.7319 | None |
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+ | 0.5419 | 0.74 | 4000 | 0.5891 | 0.6714 | 0.5567 | 0.8456 | None |
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+ | 0.556 | 0.83 | 4500 | 0.5654 | 0.6782 | 0.5750 | 0.8265 | None |
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+ | 0.5392 | 0.92 | 5000 | 0.5516 | 0.6794 | 0.5838 | 0.8125 | None |
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+ | 0.544 | 1.02 | 5500 | 0.5342 | 0.6806 | 0.6149 | 0.7621 | None |
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+ | 0.5074 | 1.11 | 6000 | 0.5626 | 0.6824 | 0.5864 | 0.8160 | None |
 
 
 
 
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  ### Framework versions
config.toml CHANGED
@@ -1,12 +1,12 @@
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  [experiment]
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- name = "binary-28"
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  type = "binary"
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  [dataset]
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  path = "thejosango/nuha-dataset"
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  dataset_revision = "main"
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- augment_ratio = 0.0
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  undersampling_strategy = "majority"
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@@ -25,6 +25,6 @@ per_device_eval_batch_size = 8
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  gradient_accumulation_steps = 2
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  weight_decay = 0.01
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  label_smoothing_factor = 0.1
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- weighted_loss = false
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  early_stopping_patience = 5
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  early_stopping_threshold = 0.005
 
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  [experiment]
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+ name = "binary-29"
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  type = "binary"
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  [dataset]
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  path = "thejosango/nuha-dataset"
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  dataset_revision = "main"
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+ augment_ratio = 0.15
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  undersampling_strategy = "majority"
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  gradient_accumulation_steps = 2
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  weight_decay = 0.01
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  label_smoothing_factor = 0.1
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+ weighted_loss = false
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  early_stopping_patience = 5
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  early_stopping_threshold = 0.005
pytorch_model.bin CHANGED
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