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--- |
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base_model: ixa-ehu/berteus-base-cased |
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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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model-index: |
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- name: MT_authorship_new |
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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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# MT_authorship_new |
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This model is a fine-tuned version of [ixa-ehu/berteus-base-cased](https://huggingface.co/ixa-ehu/berteus-base-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6223 |
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- Accuracy: 0.6675 |
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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: 2e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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: 63715 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:-----:|:---------------:|:--------:| |
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| 0.6354 | 0.2499 | 3185 | 0.6264 | 0.6229 | |
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| 0.6219 | 0.4998 | 6370 | 0.6111 | 0.6345 | |
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| 0.611 | 0.7498 | 9555 | 0.6004 | 0.6415 | |
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| 0.6091 | 0.9997 | 12740 | 0.5952 | 0.6466 | |
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| 0.5745 | 1.2496 | 15925 | 0.5926 | 0.6520 | |
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| 0.5753 | 1.4995 | 19110 | 0.5891 | 0.6543 | |
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| 0.5749 | 1.7495 | 22295 | 0.5908 | 0.6573 | |
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| 0.5741 | 1.9994 | 25480 | 0.5822 | 0.6605 | |
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| 0.5424 | 2.2493 | 28665 | 0.5911 | 0.6603 | |
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| 0.5384 | 2.4992 | 31850 | 0.5893 | 0.6625 | |
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| 0.5367 | 2.7491 | 35035 | 0.5872 | 0.6621 | |
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| 0.5445 | 2.9991 | 38220 | 0.5846 | 0.6656 | |
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| 0.5069 | 3.2490 | 41405 | 0.6050 | 0.6652 | |
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| 0.5048 | 3.4989 | 44590 | 0.6013 | 0.6667 | |
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| 0.5129 | 3.7488 | 47775 | 0.6100 | 0.6660 | |
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| 0.5042 | 3.9987 | 50960 | 0.6020 | 0.6672 | |
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| 0.4778 | 4.2487 | 54145 | 0.6240 | 0.6674 | |
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| 0.4771 | 4.4986 | 57330 | 0.6250 | 0.6673 | |
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| 0.4749 | 4.7485 | 60515 | 0.6249 | 0.6671 | |
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| 0.478 | 4.9984 | 63700 | 0.6223 | 0.6675 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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