---
library_name: transformers
license: apache-2.0
base_model: albert/albert-xxlarge-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 180715c48bee8667d4ed3428d0c1732e
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 180715c48bee8667d4ed3428d0c1732e

This model is a fine-tuned version of [albert/albert-xxlarge-v2](https://huggingface.co/albert/albert-xxlarge-v2) on the contemmcm/amazon_reviews_2013 [cell-phone] dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4820
- Data Size: 0.125
- Epoch Runtime: 142.3290
- Accuracy: 0.3853
- F1 Macro: 0.1112

## 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    | 2.0084          | 0         | 56.0280       | 0.2252   | 0.1225   |
| No log        | 1     | 1973 | 1.4765          | 0.0078    | 61.8715       | 0.3847   | 0.1262   |
| 0.0345        | 2     | 3946 | 1.4872          | 0.0156    | 66.9257       | 0.3923   | 0.1311   |
| 1.4446        | 3     | 5919 | 1.4843          | 0.0312    | 77.8494       | 0.3853   | 0.1112   |
| 1.5734        | 4     | 7892 | 1.4921          | 0.0625    | 99.0788       | 0.3853   | 0.1112   |
| 1.4989        | 5     | 9865 | 1.4820          | 0.125     | 142.3290      | 0.3853   | 0.1112   |


### Framework versions

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