End of training

README.md

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+---
+license: mit
+base_model: xlm-roberta-large
+tags:
+- generated_from_trainer
+model-index:
+- name: mtl-xlmr-large-dsc
+  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. -->
+
+# mtl-xlmr-large-dsc
+
+This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5877
+
+## 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: 8
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.05
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss |
+|:-------------:|:-----:|:-----:|:---------------:|
+| 0.4037        | 1.0   | 3750  | 0.4181          |
+| 0.3088        | 2.0   | 7500  | 0.3605          |
+| 0.3528        | 3.0   | 11250 | 0.4657          |
+| 0.172         | 4.0   | 15000 | 0.5288          |
+| 0.005         | 5.0   | 18750 | 0.5877          |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.2.1
+- Datasets 2.19.2
+- Tokenizers 0.19.1

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