---
library_name: transformers
license: apache-2.0
base_model: albert/albert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: albert-rating-regression-rob-dset
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# albert-rating-regression-rob-dset

This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1105
- Accuracy: 0.5692
- Mse: 0.6352

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Mse    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 425  | 1.0055          | 0.5593   | 0.7025 |
| 1.153         | 2.0   | 850  | 1.0727          | 0.5318   | 0.7066 |
| 0.9044        | 3.0   | 1275 | 1.0269          | 0.5689   | 0.7080 |
| 0.6813        | 4.0   | 1700 | 1.1105          | 0.5692   | 0.6352 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1