Luca Tedeschini commited on
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MultiPRIDE-DualEncoder-MainStage-FT-it

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  1. README.md +11 -10
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [nickprock/setfit-italian-hate-speech](https://huggingface.co/nickprock/setfit-italian-hate-speech) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0244
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- - Accuracy: 0.9202
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- - F1: 0.8060
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- - Precision: 0.75
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- - Recall: 0.8710
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  ## Model description
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@@ -47,7 +47,7 @@ The following hyperparameters were used during training:
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  - learning_rate: 5e-06
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  - train_batch_size: 8
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  - eval_batch_size: 8
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- - seed: 42
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  - optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 10
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 0.0219 | 1.0 | 95 | 0.0262 | 0.9202 | 0.8060 | 0.75 | 0.8710 |
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- | 0.0255 | 2.0 | 190 | 0.0251 | 0.9202 | 0.8060 | 0.75 | 0.8710 |
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- | 0.0278 | 3.0 | 285 | 0.0249 | 0.9202 | 0.8060 | 0.75 | 0.8710 |
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- | 0.0204 | 4.0 | 380 | 0.0244 | 0.9202 | 0.8060 | 0.75 | 0.8710 |
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [nickprock/setfit-italian-hate-speech](https://huggingface.co/nickprock/setfit-italian-hate-speech) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0596
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+ - Accuracy: 0.8896
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+ - F1: 0.7188
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+ - Precision: 0.6970
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+ - Recall: 0.7419
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  ## Model description
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  - learning_rate: 5e-06
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  - train_batch_size: 8
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  - eval_batch_size: 8
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+ - seed: 85
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  - optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 10
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.0424 | 1.0 | 95 | 0.0613 | 0.8834 | 0.6984 | 0.6875 | 0.7097 |
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+ | 0.0341 | 2.0 | 190 | 0.0604 | 0.8896 | 0.7188 | 0.6970 | 0.7419 |
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+ | 0.0437 | 3.0 | 285 | 0.0604 | 0.8896 | 0.7188 | 0.6970 | 0.7419 |
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+ | 0.0374 | 4.0 | 380 | 0.0595 | 0.8896 | 0.7188 | 0.6970 | 0.7419 |
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+ | 0.0338 | 5.0 | 475 | 0.0596 | 0.8896 | 0.7188 | 0.6970 | 0.7419 |
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  ### Framework versions
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