---
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