---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: ntu_adl_span_selection_xlm
  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. -->

# ntu_adl_span_selection_xlm

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: 1.0973
- Em Accuracy: 0.7760

## 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: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Em Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:-----------:|
| 0.8796        | 1.0   | 5428  | 0.8440          | 0.7248      |
| 0.6149        | 2.0   | 10857 | 0.7918          | 0.7634      |
| 0.4143        | 3.0   | 16284 | 1.0973          | 0.7760      |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1