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---
library_name: transformers
license: apache-2.0
base_model: nickprock/setfit-italian-hate-speech
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: MultiPRIDE-DualEncoder-MainStage-it
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# MultiPRIDE-DualEncoder-MainStage-it
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.
It achieves the following results on the evaluation set:
- Loss: 0.3345
- Accuracy: 0.9141
- F1: 0.7407
- Precision: 0.8696
- Recall: 0.6452
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 150
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.7188 | 1.0 | 95 | 0.5881 | 0.8405 | 0.4091 | 0.6923 | 0.2903 |
| 0.5805 | 2.0 | 190 | 0.4346 | 0.8896 | 0.6667 | 0.7826 | 0.5806 |
| 0.4433 | 3.0 | 285 | 0.3493 | 0.9141 | 0.7586 | 0.8148 | 0.7097 |
| 0.3152 | 4.0 | 380 | 0.3066 | 0.9202 | 0.7797 | 0.8214 | 0.7419 |
| 0.2758 | 5.0 | 475 | 0.3260 | 0.9080 | 0.7170 | 0.8636 | 0.6129 |
| 0.2529 | 6.0 | 570 | 0.3228 | 0.9080 | 0.7273 | 0.8333 | 0.6452 |
| 0.157 | 7.0 | 665 | 0.3345 | 0.9141 | 0.7407 | 0.8696 | 0.6452 |
### Framework versions
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1
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