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README.md
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---
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license: mit
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base_model: xlm-roberta-base
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tags:
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- generated_from_trainer
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model-index:
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- name: ntu_adl_span_selection_xlm
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# ntu_adl_span_selection_xlm
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0973
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- Em Accuracy: 0.7760
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 4
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Em Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:-----------:|
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| 0.8796 | 1.0 | 5428 | 0.8440 | 0.7248 |
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| 0.6149 | 2.0 | 10857 | 0.7918 | 0.7634 |
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| 0.4143 | 3.0 | 16284 | 1.0973 | 0.7760 |
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### Framework versions
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- Transformers 4.34.1
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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