---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: test_linsearch_only_abstract
  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. -->

# test_linsearch_only_abstract

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: 1.2716
- Accuracy: 0.6508
- F1 Macro: 0.5942
- Precision Macro: 0.6170
- Recall Macro: 0.5858

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.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: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|
| 1.2232        | 1.0   | 2466  | 1.1574          | 0.6405   | 0.5484   | 0.5538          | 0.5608       |
| 1.0386        | 2.0   | 4932  | 1.0934          | 0.6497   | 0.5631   | 0.5712          | 0.5642       |
| 0.9215        | 3.0   | 7398  | 1.0725          | 0.6634   | 0.5933   | 0.5950          | 0.5970       |
| 0.8026        | 4.0   | 9864  | 1.0994          | 0.6532   | 0.5817   | 0.5905          | 0.5796       |
| 0.6754        | 5.0   | 12330 | 1.1462          | 0.6558   | 0.5838   | 0.5934          | 0.5806       |
| 0.5958        | 6.0   | 14796 | 1.2077          | 0.6537   | 0.5857   | 0.5963          | 0.5813       |
| 0.4924        | 7.0   | 17262 | 1.2716          | 0.6508   | 0.5942   | 0.6170          | 0.5858       |
| 0.4165        | 8.0   | 19728 | 1.3450          | 0.6450   | 0.5938   | 0.6037          | 0.5923       |
| 0.3599        | 9.0   | 22194 | 1.4048          | 0.6412   | 0.5906   | 0.6077          | 0.5812       |
| 0.3262        | 10.0  | 24660 | 1.4422          | 0.6389   | 0.5941   | 0.6032          | 0.5894       |


### Framework versions

- Transformers 4.50.1
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1