Training complete

README.md

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+---
+base_model: MMG/mlm-spanish-roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: roberta-finetuned-intention-prediction-es
+  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. -->
+
+# roberta-finetuned-intention-prediction-es
+
+This model is a fine-tuned version of [MMG/mlm-spanish-roberta-base](https://huggingface.co/MMG/mlm-spanish-roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.8935
+- Precision: 0.6851
+- Recall: 0.6851
+- F1: 0.6851
+- Accuracy: 0.6745
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 2.3195        | 1.0   | 102  | 1.7653          | 0.4977    | 0.4977 | 0.4977 | 0.4881   |
+| 1.3397        | 2.0   | 204  | 1.3826          | 0.6064    | 0.6064 | 0.6064 | 0.5933   |
+| 0.884         | 3.0   | 306  | 1.2726          | 0.6495    | 0.6495 | 0.6495 | 0.6372   |
+| 0.5805        | 4.0   | 408  | 1.3527          | 0.6571    | 0.6571 | 0.6571 | 0.6444   |
+| 0.3923        | 5.0   | 510  | 1.3805          | 0.6732    | 0.6732 | 0.6732 | 0.6600   |
+| 0.2565        | 6.0   | 612  | 1.4492          | 0.6801    | 0.6801 | 0.6801 | 0.6687   |
+| 0.1782        | 7.0   | 714  | 1.4983          | 0.6766    | 0.6766 | 0.6766 | 0.6643   |
+| 0.1196        | 8.0   | 816  | 1.5517          | 0.6840    | 0.6840 | 0.6840 | 0.6726   |
+| 0.0922        | 9.0   | 918  | 1.5745          | 0.6777    | 0.6777 | 0.6777 | 0.6658   |
+| 0.0577        | 10.0  | 1020 | 1.6238          | 0.6866    | 0.6866 | 0.6866 | 0.6748   |
+| 0.042         | 11.0  | 1122 | 1.7542          | 0.6697    | 0.6697 | 0.6697 | 0.6578   |
+| 0.0298        | 12.0  | 1224 | 1.7861          | 0.6842    | 0.6842 | 0.6842 | 0.6730   |
+| 0.0201        | 13.0  | 1326 | 1.8079          | 0.6906    | 0.6906 | 0.6906 | 0.6812   |
+| 0.0147        | 14.0  | 1428 | 1.8380          | 0.6833    | 0.6833 | 0.6833 | 0.6732   |
+| 0.0109        | 15.0  | 1530 | 1.8730          | 0.6808    | 0.6808 | 0.6808 | 0.6708   |
+| 0.0079        | 16.0  | 1632 | 1.8702          | 0.6864    | 0.6864 | 0.6864 | 0.6763   |
+| 0.0067        | 17.0  | 1734 | 1.8907          | 0.6873    | 0.6873 | 0.6873 | 0.6766   |
+| 0.0061        | 18.0  | 1836 | 1.8998          | 0.6826    | 0.6826 | 0.6826 | 0.6719   |
+| 0.0057        | 19.0  | 1938 | 1.8974          | 0.6850    | 0.6850 | 0.6850 | 0.6741   |
+| 0.0051        | 20.0  | 2040 | 1.8935          | 0.6851    | 0.6851 | 0.6851 | 0.6745   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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