metadata
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: []
de_longformer_abstr_summ
This model is a fine-tuned version of 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 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.2.1
- Datasets 2.16.1
- Tokenizers 0.15.0