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---
base_model: ixa-ehu/berteus-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: MT_authorship_new
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. -->
# MT_authorship_new
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.
It achieves the following results on the evaluation set:
- Loss: 0.6223
- Accuracy: 0.6675
## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 63715
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 0.6354 | 0.2499 | 3185 | 0.6264 | 0.6229 |
| 0.6219 | 0.4998 | 6370 | 0.6111 | 0.6345 |
| 0.611 | 0.7498 | 9555 | 0.6004 | 0.6415 |
| 0.6091 | 0.9997 | 12740 | 0.5952 | 0.6466 |
| 0.5745 | 1.2496 | 15925 | 0.5926 | 0.6520 |
| 0.5753 | 1.4995 | 19110 | 0.5891 | 0.6543 |
| 0.5749 | 1.7495 | 22295 | 0.5908 | 0.6573 |
| 0.5741 | 1.9994 | 25480 | 0.5822 | 0.6605 |
| 0.5424 | 2.2493 | 28665 | 0.5911 | 0.6603 |
| 0.5384 | 2.4992 | 31850 | 0.5893 | 0.6625 |
| 0.5367 | 2.7491 | 35035 | 0.5872 | 0.6621 |
| 0.5445 | 2.9991 | 38220 | 0.5846 | 0.6656 |
| 0.5069 | 3.2490 | 41405 | 0.6050 | 0.6652 |
| 0.5048 | 3.4989 | 44590 | 0.6013 | 0.6667 |
| 0.5129 | 3.7488 | 47775 | 0.6100 | 0.6660 |
| 0.5042 | 3.9987 | 50960 | 0.6020 | 0.6672 |
| 0.4778 | 4.2487 | 54145 | 0.6240 | 0.6674 |
| 0.4771 | 4.4986 | 57330 | 0.6250 | 0.6673 |
| 0.4749 | 4.7485 | 60515 | 0.6249 | 0.6671 |
| 0.478 | 4.9984 | 63700 | 0.6223 | 0.6675 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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