MT_authorship_new / README.md
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metadata
base_model: ixa-ehu/berteus-base-cased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: MT_authorship_new
    results: []

MT_authorship_new

This model is a fine-tuned version of 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