metadata
library_name: transformers
license: apache-2.0
base_model: allenai/longformer-base-4096
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: out_base_S
results: []
out_base_S
This model is a fine-tuned version of allenai/longformer-base-4096 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9425
- Accuracy: 0.6583
- F1: 0.6496
- Cohen Kappa: 0.4906
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Cohen Kappa |
|---|---|---|---|---|---|---|
| 0.7488 | 1.0 | 134 | 0.7795 | 0.6218 | 0.4799 | 0.5341 |
| 0.7346 | 2.0 | 268 | 0.7503 | 0.6275 | 0.6221 | 0.4471 |
| 0.617 | 3.0 | 402 | 0.7870 | 0.6667 | 0.6556 | 0.4862 |
| 0.5551 | 4.0 | 536 | 0.9548 | 0.6583 | 0.6407 | 0.4721 |
| 0.3533 | 5.0 | 670 | 0.9425 | 0.6583 | 0.6496 | 0.4906 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2