---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlm_roberta_large_test_linsearch_only_abstract
  results: []
---

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

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3349
- Accuracy: 0.6504
- F1 Macro: 0.6037
- Precision Macro: 0.6113
- Recall Macro: 0.6008

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|
| 1.2114        | 1.0    | 4931  | 1.2224          | 0.6245   | 0.5249   | 0.5555          | 0.5501       |
| 1.0885        | 2.0    | 9862  | 1.1036          | 0.6427   | 0.5596   | 0.6009          | 0.5591       |
| 0.9781        | 3.0    | 14793 | 1.0828          | 0.6491   | 0.5760   | 0.6188          | 0.5811       |
| 0.8621        | 4.0    | 19724 | 1.0956          | 0.6569   | 0.5979   | 0.6363          | 0.6014       |
| 0.7267        | 5.0    | 24655 | 1.0899          | 0.6626   | 0.5970   | 0.6088          | 0.5941       |
| 0.6066        | 6.0    | 29586 | 1.2078          | 0.6517   | 0.5928   | 0.6177          | 0.5848       |
| 0.4627        | 7.0    | 34517 | 1.3349          | 0.6504   | 0.6037   | 0.6113          | 0.6008       |
| 0.3238        | 8.0    | 39448 | 1.5315          | 0.6398   | 0.5951   | 0.6064          | 0.5891       |
| 0.224         | 9.0    | 44379 | 1.8234          | 0.6438   | 0.5936   | 0.5994          | 0.5897       |
| 0.149         | 9.9981 | 49300 | 2.0762          | 0.6442   | 0.6011   | 0.6024          | 0.6007       |


### Framework versions

- Transformers 4.50.1
- Pytorch 2.5.1+cu121
- Datasets 3.4.1
- Tokenizers 0.21.1