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---
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license: cc-by-4.0
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base_model: EMBEDDIA/crosloengual-bert
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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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- f1
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model-index:
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- name: fine_tuned_rte_croslo
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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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# fine_tuned_rte_croslo
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This model is a fine-tuned version of [EMBEDDIA/crosloengual-bert](https://huggingface.co/EMBEDDIA/crosloengual-bert) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6954
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- Accuracy: 0.6207
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- F1: 0.6090
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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: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- training_steps: 400
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
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| 0.6763 | 1.7241 | 50 | 0.7138 | 0.4483 | 0.4145 |
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| 0.5789 | 3.4483 | 100 | 0.6502 | 0.5517 | 0.5215 |
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| 0.4644 | 5.1724 | 150 | 0.6409 | 0.6552 | 0.6552 |
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| 0.3137 | 6.8966 | 200 | 0.6524 | 0.5862 | 0.5222 |
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| 0.2053 | 8.6207 | 250 | 0.6379 | 0.6552 | 0.6388 |
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| 0.1242 | 10.3448 | 300 | 0.6661 | 0.6207 | 0.6090 |
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| 0.0737 | 12.0690 | 350 | 0.6753 | 0.6207 | 0.6090 |
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| 0.0521 | 13.7931 | 400 | 0.6954 | 0.6207 | 0.6090 |
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.1.1+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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