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thejosango
/
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
Model card Files
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yazansh commited on
Commit
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1 Parent(s): c79de0c

binary-33

Browse files
Files changed (4) hide show
  1. README.md +15 -18
  2. config.toml +2 -2
  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: 0.6929572707312953
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  - name: Precision
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  type: precision
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- value: 0.6382018976512677
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  - name: Recall
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  type: recall
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- value: 0.7579900240162571
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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: 0.5309
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- - F1: 0.6930
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- - Precision: 0.6382
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- - Recall: 0.7580
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  - Support: None
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  ## Model description
@@ -62,7 +62,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
@@ -77,16 +77,13 @@ 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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- | 0.5819 | 0.37 | 500 | 0.6020 | 0.6493 | 0.5311 | 0.8352 | None |
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- | 0.5611 | 0.74 | 1000 | 0.5814 | 0.6648 | 0.5561 | 0.8263 | None |
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- | 0.5467 | 1.11 | 1500 | 0.5570 | 0.6744 | 0.5878 | 0.7911 | None |
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- | 0.5345 | 1.48 | 2000 | 0.5228 | 0.6756 | 0.6470 | 0.7068 | None |
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- | 0.5299 | 1.85 | 2500 | 0.5283 | 0.6853 | 0.6291 | 0.7526 | None |
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- | 0.5054 | 2.22 | 3000 | 0.5395 | 0.6850 | 0.6159 | 0.7717 | None |
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- | 0.5052 | 2.59 | 3500 | 0.5236 | 0.6876 | 0.6450 | 0.7362 | None |
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- | 0.5033 | 2.96 | 4000 | 0.5338 | 0.6899 | 0.6202 | 0.7774 | None |
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- | 0.4839 | 3.32 | 4500 | 0.5339 | 0.6922 | 0.6292 | 0.7691 | None |
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- | 0.4846 | 3.69 | 5000 | 0.5309 | 0.6930 | 0.6382 | 0.7580 | 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: 0.6829268292682927
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  - name: Precision
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  type: precision
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+ value: 0.6481911715897777
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  - name: Recall
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  type: recall
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+ value: 0.7215961573988546
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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: 0.5679
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+ - F1: 0.6829
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+ - Precision: 0.6482
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+ - Recall: 0.7216
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  - Support: None
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  ## Model description
 
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Support |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:-------:|
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+ | 0.5606 | 0.37 | 500 | 0.5393 | 0.6786 | 0.6092 | 0.7659 | None |
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+ | 0.5414 | 0.74 | 1000 | 0.5770 | 0.6845 | 0.5747 | 0.8463 | None |
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+ | 0.5178 | 1.11 | 1500 | 0.5384 | 0.6888 | 0.6069 | 0.7962 | None |
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+ | 0.4777 | 1.48 | 2000 | 0.5407 | 0.6926 | 0.6266 | 0.7742 | None |
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+ | 0.4752 | 1.85 | 2500 | 0.5372 | 0.6960 | 0.6138 | 0.8036 | None |
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+ | 0.3952 | 2.22 | 3000 | 0.5873 | 0.6892 | 0.6155 | 0.7829 | None |
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+ | 0.4008 | 2.59 | 3500 | 0.5679 | 0.6829 | 0.6482 | 0.7216 | None |
 
 
 
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  ### Framework versions
config.toml CHANGED
@@ -1,5 +1,5 @@
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  [experiment]
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- name = "binary-32"
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  type = "binary"
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@@ -19,7 +19,7 @@ revision = "2caf9ebc5b275737c95f8bb16953288107a7131c"
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  num_train_epochs = 30
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  warmup_steps = 0
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  lr_scheduler_type = "linear"
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- learning_rate = 1e-5
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  per_device_train_batch_size = 32
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  per_device_eval_batch_size = 32
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  gradient_accumulation_steps = 2
 
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  [experiment]
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+ name = "binary-33"
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  type = "binary"
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  num_train_epochs = 30
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  warmup_steps = 0
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  lr_scheduler_type = "linear"
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+ learning_rate = 5e-5
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  per_device_train_batch_size = 32
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  per_device_eval_batch_size = 32
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  gradient_accumulation_steps = 2
pytorch_model.bin CHANGED
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