---
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: NLP-QAModel
  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. -->

# NLP-QAModel

This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.6959
- Exact Match: 0.0
- F1: 4.2322

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1     |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:------:|
| 3.6227        | 1.0   | 6673 | 4.6959          | 0.0         | 4.2322 |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0