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MultiPRIDE-LGBT-Baseline-it

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  1. README.md +74 -0
  2. config.json +24 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: nickprock/setfit-italian-hate-speech
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: MultiPRIDE-baseline-it
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+ results: []
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+ ---
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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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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # MultiPRIDE-baseline-it
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+
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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: 0.3546
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+ - Accuracy: 0.9693
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+ - F1: 0.9153
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+ - Precision: 0.9643
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+ - Recall: 0.8710
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 67
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.5817 | 1.0 | 95 | 0.8524 | 0.8650 | 0.45 | 1.0 | 0.2903 |
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+ | 0.2861 | 2.0 | 190 | 0.2522 | 0.9571 | 0.8852 | 0.9 | 0.8710 |
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+ | 0.1572 | 3.0 | 285 | 0.2762 | 0.9632 | 0.8966 | 0.9630 | 0.8387 |
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+ | 0.0878 | 4.0 | 380 | 0.4025 | 0.9632 | 0.8966 | 0.9630 | 0.8387 |
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+ | 0.0754 | 5.0 | 475 | 0.3290 | 0.9693 | 0.9153 | 0.9643 | 0.8710 |
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+ | 0.0262 | 6.0 | 570 | 0.3922 | 0.9693 | 0.9153 | 0.9643 | 0.8710 |
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+ | 0.0003 | 7.0 | 665 | 0.4190 | 0.9693 | 0.9153 | 0.9643 | 0.8710 |
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+ | 0.0003 | 8.0 | 760 | 0.3546 | 0.9693 | 0.9153 | 0.9643 | 0.8710 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.57.3
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+ - Pytorch 2.9.1+cu128
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+ - Datasets 4.4.1
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+ - Tokenizers 0.22.1
config.json ADDED
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+ {
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "dtype": "float32",
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "transformers_version": "4.57.3",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 31102
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+ }
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