---
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
model-index:
- name: mtl-xlmr-large-dsc
  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. -->

# mtl-xlmr-large-dsc

This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5877

## 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: 4
- 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.4037        | 1.0   | 3750  | 0.4181          |
| 0.3088        | 2.0   | 7500  | 0.3605          |
| 0.3528        | 3.0   | 11250 | 0.4657          |
| 0.172         | 4.0   | 15000 | 0.5288          |
| 0.005         | 5.0   | 18750 | 0.5877          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.2.1
- Datasets 2.19.2
- Tokenizers 0.19.1