update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: xlm-roberta-base-es-base-ner
+  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-es-base-ner
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2887
+- Precision: 0.5703
+- Recall: 0.6028
+- F1: 0.5861
+- Accuracy: 0.9216
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.7989        | 1.0   | 515  | 0.4610          | 0.4365    | 0.3851 | 0.4091 | 0.8867   |
+| 0.4088        | 2.0   | 1030 | 0.3468          | 0.5133    | 0.5175 | 0.5154 | 0.9067   |
+| 0.3144        | 3.0   | 1545 | 0.3082          | 0.5492    | 0.5532 | 0.5512 | 0.9158   |
+| 0.2675        | 4.0   | 2060 | 0.2913          | 0.5627    | 0.5865 | 0.5744 | 0.9216   |
+| 0.239         | 5.0   | 2575 | 0.2887          | 0.5703    | 0.6028 | 0.5861 | 0.9216   |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.13.1+cu116
+- Datasets 2.8.0
+- Tokenizers 0.13.2