MultiPRIDE-DualEncoder-MainStage-FT-it

README.md

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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-FT-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-FT-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: 0.0318
+- Accuracy: 0.9571
+- F1: 0.8923
+- Precision: 0.8529
+- Recall: 0.9355
+
+## 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: 5e-06
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 67
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.048         | 1.0   | 95   | 0.0374          | 0.9509   | 0.875  | 0.8485    | 0.9032 |
+| 0.0457        | 2.0   | 190  | 0.0358          | 0.9509   | 0.875  | 0.8485    | 0.9032 |
+| 0.039         | 3.0   | 285  | 0.0345          | 0.9571   | 0.8889 | 0.875     | 0.9032 |
+| 0.0466        | 4.0   | 380  | 0.0334          | 0.9571   | 0.8889 | 0.875     | 0.9032 |
+| 0.0478        | 5.0   | 475  | 0.0325          | 0.9509   | 0.875  | 0.8485    | 0.9032 |
+| 0.0409        | 6.0   | 570  | 0.0323          | 0.9632   | 0.9062 | 0.8788    | 0.9355 |
+| 0.0428        | 7.0   | 665  | 0.0320          | 0.9571   | 0.8923 | 0.8529    | 0.9355 |
+| 0.0402        | 8.0   | 760  | 0.0319          | 0.9571   | 0.8923 | 0.8529    | 0.9355 |
+| 0.0377        | 9.0   | 855  | 0.0318          | 0.9571   | 0.8923 | 0.8529    | 0.9355 |
+
+
+### Framework versions
+
+- Transformers 4.57.3
+- Pytorch 2.9.1+cu128
+- Datasets 4.4.1
+- Tokenizers 0.22.1

config.json

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+{
+  "architectures": [
+    "DualEncoderForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "class_weights": [
+    1.2357723712921143,
+    5.241379261016846
+  ],
+  "classifier_dropout": null,
+  "dtype": "bfloat16",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.57.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 31102
+}

model.safetensors

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+size 443306324

training_args.bin

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+size 5969