---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: vmw-xlm-asym-lr-3e-5
  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. -->

# vmw-xlm-asym-lr-3e-5

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0812
- F1-micro: 0.2355
- F1-macro: 0.0673

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 30
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1-micro | F1-macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.0839        | 1.0   | 78   | 0.0815          | 0.2427   | 0.0888   |
| 0.0817        | 2.0   | 156  | 0.0813          | 0.2427   | 0.0888   |
| 0.0823        | 3.0   | 234  | 0.0812          | 0.2333   | 0.0509   |
| 0.0819        | 4.0   | 312  | 0.0812          | 0.2355   | 0.0673   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0