---
library_name: transformers
license: apache-2.0
base_model: albert/albert-large-v1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 3e178a39e286163561f9a670e11465a1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 3e178a39e286163561f9a670e11465a1

This model is a fine-tuned version of [albert/albert-large-v1](https://huggingface.co/albert/albert-large-v1) on the ccdv/patent-classification [abstract] dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2288
- Data Size: 1.0
- Epoch Runtime: 48.9799
- Accuracy: 0.6400
- F1 Macro: 0.5982

## 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     | 2.2511          | 0         | 3.4305        | 0.1635   | 0.0531   |
| No log        | 1     | 781   | 2.0006          | 0.0078    | 4.0544        | 0.2392   | 0.0804   |
| No log        | 2     | 1562  | 1.8515          | 0.0156    | 4.3115        | 0.3255   | 0.1657   |
| No log        | 3     | 2343  | 1.5473          | 0.0312    | 4.8879        | 0.3846   | 0.2308   |
| 0.04          | 4     | 3124  | 1.3605          | 0.0625    | 6.2615        | 0.5218   | 0.3745   |
| 1.3709        | 5     | 3905  | 1.3125          | 0.125     | 9.3563        | 0.5415   | 0.3865   |
| 1.2754        | 6     | 4686  | 1.1844          | 0.25      | 14.9678       | 0.5807   | 0.4390   |
| 1.1531        | 7     | 5467  | 1.1276          | 0.5       | 26.2589       | 0.6096   | 0.5406   |
| 1.0392        | 8.0   | 6248  | 1.0762          | 1.0       | 51.5742       | 0.6274   | 0.5668   |
| 0.9615        | 9.0   | 7029  | 1.0177          | 1.0       | 49.7864       | 0.6458   | 0.5840   |
| 0.8491        | 10.0  | 7810  | 1.0766          | 1.0       | 51.6486       | 0.6400   | 0.5918   |
| 0.745         | 11.0  | 8591  | 1.0970          | 1.0       | 51.0736       | 0.6396   | 0.5917   |
| 0.6966        | 12.0  | 9372  | 1.1589          | 1.0       | 49.6696       | 0.6464   | 0.5859   |
| 0.5373        | 13.0  | 10153 | 1.2288          | 1.0       | 48.9799       | 0.6400   | 0.5982   |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1