---
base_model: textattack/albert-base-v2-imdb
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_awesome_imdb
  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. -->

# my_awesome_imdb

This model is a fine-tuned version of [textattack/albert-base-v2-imdb](https://huggingface.co/textattack/albert-base-v2-imdb) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3257
- Accuracy: 0.9398

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1749        | 1.0   | 1563 | 0.2265          | 0.9400   |
| 0.0649        | 2.0   | 3126 | 0.3257          | 0.9398   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1