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---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: tmp
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. -->
# tmp
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4127
- Precision: 0.3197
- Recall: 0.2438
- F1: 0.2766
## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.8182 | 0.35 | 500 | 0.5251 | 0.0 | 0.0 | 0.0 |
| 0.6835 | 0.7 | 1000 | 0.4857 | 0.0 | 0.0 | 0.0 |
| 0.6643 | 1.04 | 1500 | 0.4691 | 0.0 | 0.0 | 0.0 |
| 0.6403 | 1.39 | 2000 | 0.4580 | 0.4531 | 0.0349 | 0.0647 |
| 0.5617 | 1.74 | 2500 | 0.4528 | 0.3373 | 0.0673 | 0.1122 |
| 0.4896 | 2.09 | 3000 | 0.4265 | 0.3268 | 0.1611 | 0.2158 |
| 0.4451 | 2.43 | 3500 | 0.4087 | 0.3860 | 0.1791 | 0.2447 |
| 0.416 | 2.78 | 4000 | 0.4222 | 0.2937 | 0.2224 | 0.2531 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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