End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-multilingual-cased
+tags:
+- generated_from_trainer
+datasets:
+- swiss_law_area_prediction
+metrics:
+- precision
+- recall
+- f1
+model-index:
+- name: modello_finetuning1
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: swiss_law_area_prediction
+      type: swiss_law_area_prediction
+      config: main
+      split: validation
+      args: main
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9922018189992046
+    - name: Recall
+      type: recall
+      value: 0.9901734200771951
+    - name: F1
+      type: f1
+      value: 0.9911413155243709
+---
+
+<!-- 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. -->
+
+# modello_finetuning1
+
+This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the swiss_law_area_prediction dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0506
+- Precision: 0.9922
+- Recall: 0.9902
+- F1: 0.9911
+
+## 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: 6e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
+| 0.0834        | 0.38  | 500  | 0.1812          | 0.9793    | 0.9677 | 0.9730 |
+| 0.1029        | 0.76  | 1000 | 0.0973          | 0.9875    | 0.9834 | 0.9854 |
+| 0.0066        | 1.15  | 1500 | 0.0647          | 0.9864    | 0.9886 | 0.9875 |
+| 0.0008        | 1.53  | 2000 | 0.0619          | 0.9913    | 0.9893 | 0.9902 |
+| 0.0003        | 1.91  | 2500 | 0.0506          | 0.9922    | 0.9902 | 0.9911 |
+
+
+### Framework versions
+
+- Transformers 4.36.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

config.json

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+{
+  "_name_or_path": "distilbert-base-multilingual-cased",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "Civil",
+    "1": "Criminal",
+    "2": "Public"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "Civil": 0,
+    "Criminal": 1,
+    "Public": 2
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "output_past": true,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.36.1",
+  "vocab_size": 119547
+}

model.safetensors

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+oid sha256:4dcec4c72f3ae509dd4e9398694e77d1002386071e5a1fe4446cea6d3a945302
+size 541320452

runs/Dec14_11-58-50_42914af3dc17/events.out.tfevents.1702555130.42914af3dc17.1700.2

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special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "DistilBertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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