out_base_V / README.md
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---
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_V
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. -->
# out_base_V
This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9725
- Accuracy: 0.6443
- F1: 0.6330
- Cohen Kappa: 0.4632
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-----------:|
| 0.7313 | 1.0 | 134 | 0.7851 | 0.6667 | 0.5973 | 0.5339 |
| 0.9013 | 2.0 | 268 | 0.7168 | 0.6723 | 0.6588 | 0.4886 |
| 0.5642 | 3.0 | 402 | 0.7978 | 0.6555 | 0.6411 | 0.4756 |
| 0.4911 | 4.0 | 536 | 0.9718 | 0.6611 | 0.6177 | 0.5085 |
| 0.32 | 5.0 | 670 | 0.9725 | 0.6443 | 0.6330 | 0.4632 |
### Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2