transformers safetensors albert text-classification generated_from_trainer base_model:albert/albert-base-v2 base_model:finetune:albert/albert-base-v2 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
base_model: albert-base-v2
library_name: transformers
license: apache-2.0
metrics:
- accuracy
- f1
- recall
tags:
- generated_from_trainer
model-index:
- name: albert-base-v2-Shakespear
  results: []
---

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# albert-base-v2-Shakespear

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on 2 datasets.
The first dataset consists of Shakespeare's poems, and the second consists of the CNN news dataset.

It achieves the following results on the evaluation set:
- Loss: 0.0127
- Accuracy: 0.9989
- F1: 0.9989
- Recall: 0.9989

## Model description

This model was created for text classification to determine whether a given text is in Shakespeare's style or not.
You can use this model to classify texts or as a validation metric for evaluating Shakespeare-style text generation models.
The label 'LABEL_1' indicates that the text is in Shakespeare's style, while 'LABEL_0' means that it is not.


### 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 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
| No log        | 1.0   | 226  | 0.0208          | 0.9967   | 0.9967 | 0.9967 |
| No log        | 2.0   | 452  | 0.0107          | 0.9989   | 0.9989 | 0.9989 |
| 0.027         | 3.0   | 678  | 0.0113          | 0.9989   | 0.9989 | 0.9989 |
| 0.027         | 4.0   | 904  | 0.0001          | 1.0      | 1.0    | 1.0    |
| 0.0087        | 5.0   | 1130 | 0.0121          | 0.9989   | 0.9989 | 0.9989 |
| 0.0087        | 6.0   | 1356 | 0.0123          | 0.9989   | 0.9989 | 0.9989 |
| 0.001         | 7.0   | 1582 | 0.0125          | 0.9989   | 0.9989 | 0.9989 |
| 0.001         | 8.0   | 1808 | 0.0126          | 0.9989   | 0.9989 | 0.9989 |
| 0.0           | 9.0   | 2034 | 0.0127          | 0.9989   | 0.9989 | 0.9989 |
| 0.0           | 10.0  | 2260 | 0.0127          | 0.9989   | 0.9989 | 0.9989 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
