---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: QA_SYNTH_25_SEPT_WITH_FINETUNE_1.0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# QA_SYNTH_25_SEPT_WITH_FINETUNE_1.0

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: 0.0007

## 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: 2e-05
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.3279        | 1.0   | 9675  | 0.1663          |
| 0.0487        | 2.0   | 19350 | 0.0298          |
| 0.0388        | 3.0   | 29025 | 0.0166          |
| 0.0018        | 4.0   | 38700 | 0.0089          |
| 0.0121        | 5.0   | 48375 | 0.0059          |
| 0.0021        | 6.0   | 58050 | 0.0063          |
| 0.0009        | 7.0   | 67725 | 0.0023          |
| 0.0002        | 8.0   | 77400 | 0.0055          |
| 0.0011        | 9.0   | 87075 | 0.0047          |
| 0.0           | 10.0  | 96750 | 0.0007          |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3