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---
license: cc-by-4.0
base_model: EMBEDDIA/crosloengual-bert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine_tuned_rte_croslo
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. -->
# fine_tuned_rte_croslo
This model is a fine-tuned version of [EMBEDDIA/crosloengual-bert](https://huggingface.co/EMBEDDIA/crosloengual-bert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7790
- Accuracy: 0.6207
- F1: 0.5951
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.6951 | 1.7241 | 50 | 0.6869 | 0.5517 | 0.5549 |
| 0.5952 | 3.4483 | 100 | 0.6381 | 0.6207 | 0.5466 |
| 0.4725 | 5.1724 | 150 | 0.6293 | 0.6207 | 0.6090 |
| 0.3055 | 6.8966 | 200 | 0.6905 | 0.6552 | 0.6018 |
| 0.2004 | 8.6207 | 250 | 0.6624 | 0.6897 | 0.6523 |
| 0.1191 | 10.3448 | 300 | 0.7124 | 0.6552 | 0.6236 |
| 0.0661 | 12.0690 | 350 | 0.7694 | 0.6552 | 0.6236 |
| 0.048 | 13.7931 | 400 | 0.7790 | 0.6207 | 0.5951 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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