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README.md
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---
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library_name: transformers
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license: mit
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base_model: FacebookAI/xlm-roberta-large
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: XLMRoberta-TASS-v2-2026
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# XLMRoberta-TASS-v2-2026
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9640
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- F1 Macro: 0.5098
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- F1 Weighted: 0.5186
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- Accuracy: 0.5630
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 16
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.15
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- num_epochs: 6
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- label_smoothing_factor: 0.1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|
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| 1.1069 | 1.0 | 241 | 1.0931 | 0.3048 | 0.3239 | 0.3694 |
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| 1.1106 | 2.0 | 482 | 1.0892 | 0.1878 | 0.2211 | 0.3923 |
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| 1.0845 | 3.0 | 723 | 1.0726 | 0.3716 | 0.3849 | 0.4807 |
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| 1.081 | 4.0 | 964 | 1.0165 | 0.4088 | 0.4198 | 0.5182 |
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| 1.0413 | 5.0 | 1205 | 0.9810 | 0.4980 | 0.5061 | 0.5546 |
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| 1.036 | 6.0 | 1446 | 0.9640 | 0.5098 | 0.5186 | 0.5630 |
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### Framework versions
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- Transformers 4.57.1
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- Pytorch 2.7.1+cu118
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- Datasets 4.2.0
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- Tokenizers 0.22.1
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