---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: fine-tuned-DatasetQAS-Squad-ID-with-xlm-roberta-large-without-ITTL-without-freeze-LR-1e-05
  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-DatasetQAS-Squad-ID-with-xlm-roberta-large-without-ITTL-without-freeze-LR-1e-05

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: 1.3876
- Exact Match: 53.6102
- F1: 69.6077

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 64
- 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      |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
| 1.5313        | 0.5   | 463  | 1.4235          | 48.7014     | 66.1658 |
| 1.3868        | 1.0   | 926  | 1.3193          | 51.7189     | 68.5896 |
| 1.2618        | 1.5   | 1389 | 1.2877          | 52.8032     | 69.3561 |
| 1.1847        | 2.0   | 1852 | 1.2893          | 53.0218     | 69.7724 |
| 1.0884        | 2.5   | 2315 | 1.2777          | 53.3328     | 69.8210 |
| 1.0927        | 3.0   | 2778 | 1.2596          | 53.4000     | 69.9664 |
| 0.9519        | 3.5   | 3241 | 1.3342          | 53.6102     | 69.6168 |
| 0.9591        | 4.0   | 3704 | 1.3078          | 54.0640     | 69.9492 |
| 0.8586        | 4.49  | 4167 | 1.3876          | 53.6102     | 69.6077 |


### Framework versions

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