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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-LPFT-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-LPFT-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: 0.0258
- Accuracy: 0.9202
- F1: 0.8060
- Precision: 0.75
- Recall: 0.8710
## 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: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1876 | 1.0 | 95 | 0.1464 | 0.8037 | 0.3043 | 0.4667 | 0.2258 |
| 0.1365 | 2.0 | 190 | 0.1072 | 0.8773 | 0.6667 | 0.6897 | 0.6452 |
| 0.112 | 3.0 | 285 | 0.0677 | 0.8957 | 0.7302 | 0.7188 | 0.7419 |
| 0.0535 | 4.0 | 380 | 0.0465 | 0.9141 | 0.7742 | 0.7742 | 0.7742 |
| 0.036 | 5.0 | 475 | 0.0335 | 0.8957 | 0.7385 | 0.7059 | 0.7742 |
| 0.0322 | 6.0 | 570 | 0.0299 | 0.9141 | 0.7879 | 0.7429 | 0.8387 |
| 0.0239 | 7.0 | 665 | 0.0274 | 0.9202 | 0.8060 | 0.75 | 0.8710 |
| 0.0275 | 8.0 | 760 | 0.0263 | 0.9202 | 0.8060 | 0.75 | 0.8710 |
| 0.0289 | 9.0 | 855 | 0.0259 | 0.9202 | 0.8060 | 0.75 | 0.8710 |
| 0.0206 | 10.0 | 950 | 0.0258 | 0.9202 | 0.8060 | 0.75 | 0.8710 |
### Framework versions
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1
|