update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: xlm-r-base-leyzer-en-intent
+  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-r-base-leyzer-en-intent
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1995
+- Accuracy: 0.9624
+- F1: 0.9624
+
+## 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: 7
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 1.9235        | 1.0   | 1061 | 1.5991          | 0.6680   | 0.6680 |
+| 0.8738        | 2.0   | 2122 | 0.7982          | 0.8359   | 0.8359 |
+| 0.4406        | 3.0   | 3183 | 0.4689          | 0.9132   | 0.9132 |
+| 0.2534        | 4.0   | 4244 | 0.3165          | 0.9360   | 0.9360 |
+| 0.1593        | 5.0   | 5305 | 0.2434          | 0.9507   | 0.9507 |
+| 0.108         | 6.0   | 6366 | 0.2104          | 0.9599   | 0.9599 |
+| 0.0914        | 7.0   | 7427 | 0.1995          | 0.9624   | 0.9624 |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.13.0+cu116
+- Datasets 2.8.0
+- Tokenizers 0.13.2