haspeech_ita / README.md
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haspeech_ita
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---
license: gpl-3.0
base_model: MilaNLProc/hate-ita-xlm-r-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: haspeech_ita
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. -->
# haspeech_ita
This model is a fine-tuned version of [MilaNLProc/hate-ita-xlm-r-large](https://huggingface.co/MilaNLProc/hate-ita-xlm-r-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0250
- F1 Macro: 0.9966
- Accuracy: 0.9973
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.4001 | 0.48 | 100 | 0.1722 | 0.9198 | 0.9377 |
| 0.1669 | 0.96 | 200 | 0.0355 | 0.9865 | 0.9892 |
| 0.0824 | 1.44 | 300 | 0.0839 | 0.9864 | 0.9892 |
| 0.0672 | 1.92 | 400 | 0.0277 | 0.9933 | 0.9946 |
| 0.0761 | 2.4 | 500 | 0.0483 | 0.9933 | 0.9946 |
| 0.0413 | 2.88 | 600 | 0.0250 | 0.9966 | 0.9973 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1
- Datasets 2.15.0
- Tokenizers 0.15.0