---
library_name: transformers
license: mit
base_model: deepset/gbert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bea-2way-full
  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. -->

# bea-2way-full

This model is a fine-tuned version of [deepset/gbert-base](https://huggingface.co/deepset/gbert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4846
- N Samples: 827.0
- Accuracy: 0.8452
- Precision Macro: 0.8134
- Recall Macro: 0.8163
- F1 Macro: 0.8148
- Qwk: 0.6297

## 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: 8
- eval_batch_size: 16
- seed: 42
- 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: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | N Samples | Accuracy | Precision Macro | Recall Macro | F1 Macro | Qwk    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:--------:|:---------------:|:------------:|:--------:|:------:|
| 0.5195        | 1.0   | 884  | 0.4426          | 827.0     | 0.7956   | 0.7553          | 0.7431       | 0.7485   | 0.4974 |
| 0.4061        | 2.0   | 1768 | 0.4384          | 827.0     | 0.8259   | 0.8085          | 0.7526       | 0.7717   | 0.5469 |
| 0.2922        | 3.0   | 2652 | 0.4846          | 827.0     | 0.8452   | 0.8134          | 0.8163       | 0.8148   | 0.6297 |


### Framework versions

- Transformers 5.1.0
- Pytorch 2.10.0+cu128
- Datasets 4.6.1
- Tokenizers 0.22.2