initial_model
This model is a fine-tuned version of docketanalyzer/docket-lm-xs on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0187
- F1: 0.9938
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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 30
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
0.2297 | 0.0533 | 60 | 0.1805 | 0.9693 |
0.1411 | 0.1067 | 120 | 0.0593 | 0.9850 |
0.0099 | 0.16 | 180 | 0.0447 | 0.9908 |
0.0348 | 0.2133 | 240 | 0.0474 | 0.9892 |
0.0046 | 0.2667 | 300 | 0.0379 | 0.9923 |
0.0031 | 0.32 | 360 | 0.0334 | 0.9938 |
0.127 | 0.3733 | 420 | 0.0325 | 0.9933 |
0.1795 | 0.4267 | 480 | 0.0325 | 0.9928 |
0.0023 | 0.48 | 540 | 0.0364 | 0.9933 |
0.0028 | 0.5333 | 600 | 0.0353 | 0.9923 |
0.0043 | 0.5867 | 660 | 0.0290 | 0.9933 |
0.1299 | 0.64 | 720 | 0.0252 | 0.9938 |
0.188 | 0.6933 | 780 | 0.0235 | 0.9933 |
0.0019 | 0.7467 | 840 | 0.0208 | 0.9938 |
0.002 | 0.8 | 900 | 0.0199 | 0.9938 |
0.0525 | 0.8533 | 960 | 0.0192 | 0.9938 |
0.008 | 0.9067 | 1020 | 0.0190 | 0.9938 |
0.0013 | 0.96 | 1080 | 0.0193 | 0.9938 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.14.4
- Tokenizers 0.19.1
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