---
library_name: transformers
license: apache-2.0
base_model: albert/albert-base-v1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: a58af9b811decb15de671183c4b54b07
  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. -->

# a58af9b811decb15de671183c4b54b07

This model is a fine-tuned version of [albert/albert-base-v1](https://huggingface.co/albert/albert-base-v1) on the contemmcm/amazon_reviews_2013 [cell-phone] dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8621
- Data Size: 1.0
- Epoch Runtime: 72.8094
- Accuracy: 0.6829
- F1 Macro: 0.6121

## 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
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|
| No log        | 0     | 0     | 1.7944          | 0         | 5.8050        | 0.1102   | 0.0716   |
| No log        | 1     | 1973  | 1.4652          | 0.0078    | 6.7679        | 0.3875   | 0.1904   |
| 0.0319        | 2     | 3946  | 1.3011          | 0.0156    | 7.0154        | 0.4623   | 0.2680   |
| 1.1769        | 3     | 5919  | 1.1409          | 0.0312    | 7.9874        | 0.5376   | 0.3510   |
| 0.9719        | 4     | 7892  | 0.9420          | 0.0625    | 9.9755        | 0.6041   | 0.4954   |
| 0.8939        | 5     | 9865  | 0.8626          | 0.125     | 14.2018       | 0.6356   | 0.5305   |
| 0.8639        | 6     | 11838 | 0.8189          | 0.25      | 22.6114       | 0.6580   | 0.5508   |
| 0.8509        | 7     | 13811 | 0.7834          | 0.5       | 39.4226       | 0.6698   | 0.6019   |
| 0.7676        | 8.0   | 15784 | 0.7777          | 1.0       | 73.1966       | 0.6729   | 0.6116   |
| 0.6876        | 9.0   | 17757 | 0.7524          | 1.0       | 74.0192       | 0.6952   | 0.6125   |
| 0.6258        | 10.0  | 19730 | 0.7636          | 1.0       | 75.1704       | 0.6802   | 0.6244   |
| 0.6055        | 11.0  | 21703 | 0.7913          | 1.0       | 73.2826       | 0.6909   | 0.6220   |
| 0.5316        | 12.0  | 23676 | 0.7981          | 1.0       | 73.7851       | 0.6908   | 0.6192   |
| 0.4656        | 13.0  | 25649 | 0.8621          | 1.0       | 72.8094       | 0.6829   | 0.6121   |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.2.0
- Tokenizers 0.22.1