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---
license: mit
base_model: vicgalle/xlm-roberta-large-xnli-anli
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlm-roberta-large-xnli-anli-v5.0
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. -->
# xlm-roberta-large-xnli-anli-v5.0
This model is a fine-tuned version of [vicgalle/xlm-roberta-large-xnli-anli](https://huggingface.co/vicgalle/xlm-roberta-large-xnli-anli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5120
- F1 Macro: 0.8215
- F1 Micro: 0.8223
- Accuracy Balanced: 0.8216
- Accuracy: 0.8223
- Precision Macro: 0.8215
- Recall Macro: 0.8216
- Precision Micro: 0.8223
- Recall Micro: 0.8223
## 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: 9e-06
- train_batch_size: 8
- eval_batch_size: 64
- seed: 40
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
| 0.3779 | 0.85 | 200 | 0.4494 | 0.8020 | 0.8020 | 0.8084 | 0.8020 | 0.8088 | 0.8084 | 0.8020 | 0.8020 |
| 0.2646 | 1.69 | 400 | 0.4425 | 0.8113 | 0.8121 | 0.8126 | 0.8121 | 0.8108 | 0.8126 | 0.8121 | 0.8121 |
| 0.1961 | 2.54 | 600 | 0.5222 | 0.8131 | 0.8147 | 0.8129 | 0.8147 | 0.8135 | 0.8129 | 0.8147 | 0.8147 |
### eval result
|Datasets|asadfgglie/nli-zh-tw-all/test|asadfgglie/BanBan_2024-10-17-facial_expressions-nli/test|eval_dataset|test_dataset|
| :---: | :---: | :---: | :---: | :---: |
|eval_loss|0.541|0.26|0.517|0.512|
|eval_f1_macro|0.809|0.918|0.814|0.822|
|eval_f1_micro|0.81|0.918|0.815|0.822|
|eval_accuracy_balanced|0.809|0.918|0.815|0.822|
|eval_accuracy|0.81|0.918|0.815|0.822|
|eval_precision_macro|0.809|0.918|0.814|0.821|
|eval_recall_macro|0.809|0.918|0.815|0.822|
|eval_precision_micro|0.81|0.918|0.815|0.822|
|eval_recall_micro|0.81|0.918|0.815|0.822|
|eval_runtime|50.716|0.611|11.113|44.249|
|eval_samples_per_second|167.6|1548.868|169.977|170.785|
|eval_steps_per_second|2.622|24.559|2.699|2.689|
|Size of dataset|8500|946|1889|7557|
### Framework versions
- Transformers 4.33.3
- Pytorch 2.5.1+cu121
- Datasets 2.14.7
- Tokenizers 0.13.3
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