increase a lot performance with italian base bert!

README.md

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+---
+library_name: transformers
+base_model: Musixmatch/umberto-wikipedia-uncased-v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: umberto-wikipedia-uncased-v1-finetuned-emotions
+  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. -->
+
+# umberto-wikipedia-uncased-v1-finetuned-emotions
+
+This model is a fine-tuned version of [Musixmatch/umberto-wikipedia-uncased-v1](https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7553
+- Accuracy: 0.5644
+- F1: 0.5295
+
+## 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: 64
+- eval_batch_size: 64
+- 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 | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| No log        | 1.0   | 29   | 1.7744          | 0.1994   | 0.1058 |
+| No log        | 2.0   | 58   | 1.7553          | 0.5644   | 0.5295 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 3.0.0
+- Tokenizers 0.19.1