---
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
model-index:
- name: xlmrlarge-webis
  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. -->

# xlmrlarge-webis

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: 5.6078

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 200  | 2.7023          |
| No log        | 2.0   | 400  | 2.5847          |
| 2.5797        | 3.0   | 600  | 2.7460          |
| 2.5797        | 4.0   | 800  | 3.3822          |
| 0.8578        | 5.0   | 1000 | 3.8268          |
| 0.8578        | 6.0   | 1200 | 4.4783          |
| 0.8578        | 7.0   | 1400 | 5.0087          |
| 0.2619        | 8.0   | 1600 | 5.5192          |
| 0.2619        | 9.0   | 1800 | 5.5585          |
| 0.1092        | 10.0  | 2000 | 5.6078          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1