| | --- |
| | base_model: LennartKeller/longformer-gottbert-base-8192-aw512 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: de_longformer_abstr_summ |
| | 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. --> |
| |
|
| | # de_longformer_abstr_summ |
| | |
| | This model is a fine-tuned version of [LennartKeller/longformer-gottbert-base-8192-aw512](https://huggingface.co/LennartKeller/longformer-gottbert-base-8192-aw512) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5746 |
| | - Precision: 0.1612 |
| | - Recall: 0.2474 |
| | - F1: 0.1952 |
| | - Accuracy: 0.7800 |
| | |
| | ## 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: 2 |
| | - eval_batch_size: 2 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 8 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | No log | 0.98 | 48 | 0.5548 | 0.0 | 0.0 | 0.0 | 0.7540 | |
| | | No log | 1.99 | 97 | 0.5185 | 0.1067 | 0.1548 | 0.1263 | 0.7864 | |
| | | No log | 2.99 | 146 | 0.5068 | 0.0876 | 0.1534 | 0.1115 | 0.7806 | |
| | | No log | 4.0 | 195 | 0.5145 | 0.2797 | 0.3889 | 0.3254 | 0.7926 | |
| | | No log | 4.98 | 243 | 0.5097 | 0.2068 | 0.3439 | 0.2583 | 0.7916 | |
| | | No log | 5.99 | 292 | 0.5073 | 0.1637 | 0.2831 | 0.2075 | 0.7920 | |
| | | No log | 6.99 | 341 | 0.5316 | 0.1723 | 0.2553 | 0.2058 | 0.7865 | |
| | | No log | 8.0 | 390 | 0.5480 | 0.1483 | 0.2275 | 0.1795 | 0.7837 | |
| | | No log | 8.98 | 438 | 0.5587 | 0.1649 | 0.2725 | 0.2055 | 0.7823 | |
| | | No log | 9.85 | 480 | 0.5746 | 0.1612 | 0.2474 | 0.1952 | 0.7800 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.36.2 |
| | - Pytorch 2.2.1 |
| | - Datasets 2.16.1 |
| | - Tokenizers 0.15.0 |
| |
|
