End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: xlm-roberta-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: sentiment-roberta-es-2025-II
+  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. -->
+
+# sentiment-roberta-es-2025-II
+
+This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8121
+- Accuracy: 0.8826
+- Precision: 0.8829
+- Recall: 0.8826
+- F1: 0.8820
+
+## 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: 1e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.6043        | 1.0   | 656  | 0.6682          | 0.8826   | 0.8824    | 0.8826 | 0.8825 |
+| 0.5065        | 2.0   | 1312 | 0.6298          | 0.8720   | 0.8721    | 0.8720 | 0.8720 |
+| 0.4613        | 3.0   | 1968 | 0.6470          | 0.8826   | 0.8889    | 0.8826 | 0.8832 |
+| 0.2488        | 4.0   | 2624 | 0.7832          | 0.8765   | 0.8811    | 0.8765 | 0.8771 |
+| 0.149         | 5.0   | 3280 | 0.8121          | 0.8826   | 0.8829    | 0.8826 | 0.8820 |
+
+
+### Framework versions
+
+- Transformers 4.57.1
+- Pytorch 2.8.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.1

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