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---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: edos-2023-baseline-xlm-roberta-base-label_category
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. -->
# edos-2023-baseline-xlm-roberta-base-label_category
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6064
- F1: 0.7577
## 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: 46
- eval_batch_size: 46
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.2018 | 1.69 | 100 | 1.1031 | 0.1623 |
| 1.0526 | 3.39 | 200 | 0.9000 | 0.5621 |
| 0.9025 | 5.08 | 300 | 0.7649 | 0.6131 |
| 0.8141 | 6.78 | 400 | 0.6715 | 0.7132 |
| 0.7435 | 8.47 | 500 | 0.6064 | 0.7577 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
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