---
library_name: transformers
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: AMANDA
  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. -->

# AMANDA

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4717
- Accuracy: 0.8243

## 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: 5e-05
- train_batch_size: 16
- 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: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.2389        | 0.0769 | 5    | 0.8651          | 0.8243   |
| 0.6616        | 0.1538 | 10   | 0.6137          | 0.8243   |
| 0.3941        | 0.2308 | 15   | 0.6143          | 0.8243   |
| 0.6576        | 0.3077 | 20   | 0.5270          | 0.8243   |
| 0.4628        | 0.3846 | 25   | 0.4904          | 0.8243   |
| 0.4493        | 0.4615 | 30   | 0.5351          | 0.8243   |
| 0.5603        | 0.5385 | 35   | 0.5049          | 0.8243   |
| 0.5586        | 0.6154 | 40   | 0.4949          | 0.8243   |
| 0.528         | 0.6923 | 45   | 0.4784          | 0.8243   |
| 0.6357        | 0.7692 | 50   | 0.4717          | 0.8243   |
| 0.4228        | 0.8462 | 55   | 0.4674          | 0.8243   |
| 0.4739        | 0.9231 | 60   | 0.4616          | 0.8243   |
| 0.4855        | 1.0    | 65   | 0.4503          | 0.8243   |
| 0.6234        | 1.0769 | 70   | 0.4921          | 0.8243   |
| 0.5158        | 1.1538 | 75   | 0.4351          | 0.8243   |
| 0.3356        | 1.2308 | 80   | 0.4576          | 0.8243   |
| 0.4118        | 1.3077 | 85   | 0.4457          | 0.8243   |
| 0.39          | 1.3846 | 90   | 0.4153          | 0.8243   |
| 0.3848        | 1.4615 | 95   | 0.4377          | 0.8243   |
| 0.3499        | 1.5385 | 100  | 0.4427          | 0.8209   |
| 0.3776        | 1.6154 | 105  | 0.3825          | 0.8446   |
| 0.4228        | 1.6923 | 110  | 0.3755          | 0.8345   |
| 0.3157        | 1.7692 | 115  | 0.4031          | 0.8243   |
| 0.3163        | 1.8462 | 120  | 0.4938          | 0.8277   |
| 0.504         | 1.9231 | 125  | 0.4861          | 0.8277   |
| 0.4722        | 2.0    | 130  | 0.4717          | 0.8243   |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1