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_W
results: []
out_base_W
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: 1.0009
- Accuracy: 0.6471
- F1: 0.6242
- Cohen Kappa: 0.4456
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 |
|---|---|---|---|---|---|---|
| 0.7956 | 1.0 | 134 | 0.7777 | 0.6499 | 0.5946 | 0.4277 |
| 0.7351 | 2.0 | 268 | 0.7918 | 0.5854 | 0.5813 | 0.3401 |
| 0.5332 | 3.0 | 402 | 0.7313 | 0.6471 | 0.6191 | 0.4461 |
| 0.5739 | 4.0 | 536 | 0.9479 | 0.6359 | 0.5965 | 0.4022 |
| 0.3323 | 5.0 | 670 | 1.0009 | 0.6471 | 0.6242 | 0.4456 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2