End of training

README.md

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+---
+license: mit
+base_model: xlm-roberta-base
+tags:
+- generated_from_trainer
+datasets:
+- wmt20_mlqe_task1
+model-index:
+- name: xlmr-ne-en-no_shuffled-orig-test1000
+  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. -->
+
+# xlmr-ne-en-no_shuffled-orig-test1000
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the wmt20_mlqe_task1 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5471
+- R Squared: 0.2194
+- Mae: 0.5682
+- Pearson R: 0.6846
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | R Squared | Mae    | Pearson R |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---------:|
+| No log        | 1.0   | 438  | 0.5304          | 0.2432    | 0.5810 | 0.6277    |
+| 0.7677        | 2.0   | 876  | 0.4347          | 0.3798    | 0.5171 | 0.6653    |
+| 0.5573        | 3.0   | 1314 | 0.5234          | 0.2531    | 0.5506 | 0.6777    |
+| 0.4018        | 4.0   | 1752 | 0.5984          | 0.1462    | 0.5975 | 0.6819    |
+| 0.2964        | 5.0   | 2190 | 0.5471          | 0.2194    | 0.5682 | 0.6846    |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.6
+- Tokenizers 0.14.1