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--- |
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license: apache-2.0 |
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base_model: docketanalyzer/docket-lm-xs |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: initial_model |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# initial_model |
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This model is a fine-tuned version of [docketanalyzer/docket-lm-xs](https://huggingface.co/docketanalyzer/docket-lm-xs) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0187 |
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- F1: 0.9938 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 30 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| 0.2297 | 0.0533 | 60 | 0.1805 | 0.9693 | |
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| 0.1411 | 0.1067 | 120 | 0.0593 | 0.9850 | |
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| 0.0099 | 0.16 | 180 | 0.0447 | 0.9908 | |
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| 0.0348 | 0.2133 | 240 | 0.0474 | 0.9892 | |
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| 0.0046 | 0.2667 | 300 | 0.0379 | 0.9923 | |
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| 0.0031 | 0.32 | 360 | 0.0334 | 0.9938 | |
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| 0.127 | 0.3733 | 420 | 0.0325 | 0.9933 | |
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| 0.1795 | 0.4267 | 480 | 0.0325 | 0.9928 | |
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| 0.0023 | 0.48 | 540 | 0.0364 | 0.9933 | |
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| 0.0028 | 0.5333 | 600 | 0.0353 | 0.9923 | |
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| 0.0043 | 0.5867 | 660 | 0.0290 | 0.9933 | |
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| 0.1299 | 0.64 | 720 | 0.0252 | 0.9938 | |
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| 0.188 | 0.6933 | 780 | 0.0235 | 0.9933 | |
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| 0.0019 | 0.7467 | 840 | 0.0208 | 0.9938 | |
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| 0.002 | 0.8 | 900 | 0.0199 | 0.9938 | |
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| 0.0525 | 0.8533 | 960 | 0.0192 | 0.9938 | |
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| 0.008 | 0.9067 | 1020 | 0.0190 | 0.9938 | |
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| 0.0013 | 0.96 | 1080 | 0.0193 | 0.9938 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.14.4 |
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- Tokenizers 0.19.1 |
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