End of training

README.md

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+---
+library_name: transformers
+base_model: MatteoFasulo/xlm-roberta-base_69
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: xlm-roberta-base_69
+  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. -->
+
+# xlm-roberta-base_69
+
+This model is a fine-tuned version of [MatteoFasulo/xlm-roberta-base_69](https://huggingface.co/MatteoFasulo/xlm-roberta-base_69) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4990
+- F1-score: 0.8549
+- Accuracy: 0.8549
+- Precision: 0.8549
+- Recall: 0.8550
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 69
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1-score | Accuracy | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|
+| No log        | 1.0   | 379  | 0.4454          | 0.8611   | 0.8611   | 0.8620    | 0.8615 |
+| 0.3451        | 2.0   | 758  | 0.4597          | 0.8469   | 0.8472   | 0.8488    | 0.8467 |
+| 0.3027        | 3.0   | 1137 | 0.4418          | 0.8472   | 0.8472   | 0.8474    | 0.8474 |
+| 0.2931        | 4.0   | 1516 | 0.5016          | 0.8392   | 0.8395   | 0.8444    | 0.8404 |
+| 0.2931        | 5.0   | 1895 | 0.4875          | 0.8565   | 0.8565   | 0.8573    | 0.8569 |
+| 0.2469        | 6.0   | 2274 | 0.4990          | 0.8549   | 0.8549   | 0.8549    | 0.8550 |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0

config.json

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+{
+  "_name_or_path": "MatteoFasulo/xlm-roberta-base_69",
+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "NEG",
+    "1": "POS"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "NEG": 0,
+    "POS": 1
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.47.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

model.safetensors

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+size 1112205008

training_args.bin

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+size 5304