---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: fine-tuned-QAS-Squad_2-with-xlm-roberta-large
  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. -->

# fine-tuned-QAS-Squad_2-with-xlm-roberta-large

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: 0.8615
- Exact Match: 69.2340
- F1: 82.5542

## 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: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1      |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
| 1.0967        | 0.5   | 464  | 1.0076          | 57.8908     | 71.8971 |
| 0.912         | 1.0   | 928  | 0.8118          | 65.0306     | 79.0193 |
| 0.8071        | 1.5   | 1392 | 0.7587          | 67.2288     | 80.3986 |
| 0.7414        | 2.0   | 1856 | 0.7322          | 68.3614     | 81.3949 |
| 0.6548        | 2.5   | 2320 | 0.7685          | 67.5896     | 81.3012 |
| 0.624         | 3.0   | 2784 | 0.7307          | 68.5544     | 82.0875 |
| 0.5412        | 3.5   | 3248 | 0.7606          | 69.2340     | 82.4384 |
| 0.5356        | 4.0   | 3712 | 0.7352          | 69.5612     | 82.7509 |
| 0.4463        | 4.5   | 4176 | 0.7862          | 69.2843     | 82.3298 |
| 0.4899        | 5.0   | 4640 | 0.7868          | 69.5109     | 82.7397 |
| 0.417         | 5.5   | 5104 | 0.8615          | 69.2340     | 82.5542 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2