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---

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

# test_trainer



This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on an unknown dataset.

It achieves the following results on the evaluation set:

- Loss: 0.9995

- Accuracy: 0.581



## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH 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 | Accuracy |

|:-------------:|:-----:|:----:|:---------------:|:--------:|

| No log        | 1.0   | 125  | 1.3630          | 0.414    |

| No log        | 2.0   | 250  | 1.0149          | 0.55     |

| No log        | 3.0   | 375  | 0.9995          | 0.581    |





### Framework versions



- Transformers 4.46.0

- Pytorch 2.5.0+cu124

- Datasets 3.0.2

- Tokenizers 0.20.1