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---
library_name: transformers
license: apache-2.0
base_model: albert/albert-base-v1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: classification_model_albert
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. -->
# classification_model_albert
This model is a fine-tuned version of [albert/albert-base-v1](https://huggingface.co/albert/albert-base-v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2353
- Accuracy: 0.9224
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2452 | 1.0 | 1563 | 0.2077 | 0.9186 |
| 0.1795 | 2.0 | 3126 | 0.2353 | 0.9224 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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