output_LiLT_test_03
This model is a fine-tuned version of nielsr/lilt-xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1452
- Precision: 0.7549
- Recall: 0.8276
- F1: 0.7896
- Accuracy: 0.9577
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 45
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 0.0808 | 100 | 0.5589 | 0.0259 | 0.0020 | 0.0037 | 0.8724 |
| No log | 0.1617 | 200 | 0.3198 | 0.3704 | 0.3698 | 0.3701 | 0.9009 |
| No log | 0.2425 | 300 | 0.2222 | 0.6005 | 0.6743 | 0.6353 | 0.9346 |
| No log | 0.3234 | 400 | 0.1950 | 0.7231 | 0.6316 | 0.6743 | 0.9446 |
| 0.4262 | 0.4042 | 500 | 0.1684 | 0.7115 | 0.7215 | 0.7165 | 0.9491 |
| 0.4262 | 0.4850 | 600 | 0.1885 | 0.6328 | 0.7602 | 0.6907 | 0.9366 |
| 0.4262 | 0.5659 | 700 | 0.1776 | 0.6609 | 0.8097 | 0.7278 | 0.9437 |
| 0.4262 | 0.6467 | 800 | 0.2086 | 0.6420 | 0.8034 | 0.7137 | 0.9398 |
| 0.4262 | 0.7276 | 900 | 0.1702 | 0.8241 | 0.7469 | 0.7836 | 0.9611 |
| 0.1027 | 0.8084 | 1000 | 0.1496 | 0.8028 | 0.7558 | 0.7786 | 0.9601 |
| 0.1027 | 0.8892 | 1100 | 0.1620 | 0.7354 | 0.7754 | 0.7549 | 0.9513 |
| 0.1027 | 0.9701 | 1200 | 0.1404 | 0.8062 | 0.7997 | 0.8029 | 0.9627 |
| 0.1027 | 1.0509 | 1300 | 0.1626 | 0.7976 | 0.7564 | 0.7764 | 0.9597 |
| 0.1027 | 1.1318 | 1400 | 0.1741 | 0.7253 | 0.8089 | 0.7648 | 0.9485 |
| 0.0764 | 1.2126 | 1500 | 0.1278 | 0.8170 | 0.7798 | 0.7979 | 0.9645 |
| 0.0764 | 1.2935 | 1600 | 0.1452 | 0.7549 | 0.8276 | 0.7896 | 0.9577 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
nielsr/lilt-xlm-roberta-base