---
library_name: transformers
license: apache-2.0
base_model: albert/albert-xxlarge-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- rouge
model-index:
- name: 6092b68db85e70fdf09a4e82345627f1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 6092b68db85e70fdf09a4e82345627f1

This model is a fine-tuned version of [albert/albert-xxlarge-v2](https://huggingface.co/albert/albert-xxlarge-v2) on the google/boolq dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6649
- Data Size: 1.0
- Epoch Runtime: 95.4464
- Accuracy: 0.6213
- F1 Macro: 0.3832
- Rouge1: 0.6213
- Rouge2: 0.0
- Rougel: 0.6207
- Rougelsum: 0.6210

## 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 | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|:------:|:------:|:------:|:---------:|
| No log        | 0     | 0    | 0.7116          | 0         | 8.5900        | 0.5012   | 0.4998   | 0.5006 | 0.0    | 0.5012 | 0.5015    |
| No log        | 1     | 294  | 0.7004          | 0.0078    | 9.2705        | 0.5450   | 0.4684   | 0.5453 | 0.0    | 0.5447 | 0.5447    |
| No log        | 2     | 588  | 0.6827          | 0.0156    | 9.8441        | 0.6210   | 0.3854   | 0.6210 | 0.0    | 0.6207 | 0.6207    |
| No log        | 3     | 882  | 0.6780          | 0.0312    | 11.1787       | 0.6088   | 0.4021   | 0.6086 | 0.0    | 0.6081 | 0.6088    |
| 0.0292        | 4     | 1176 | 0.6674          | 0.0625    | 13.4752       | 0.6213   | 0.3832   | 0.6213 | 0.0    | 0.6207 | 0.6210    |
| 0.0551        | 5     | 1470 | 0.6646          | 0.125     | 17.7182       | 0.6213   | 0.3832   | 0.6213 | 0.0    | 0.6207 | 0.6210    |
| 0.1025        | 6     | 1764 | 0.6689          | 0.25      | 26.6261       | 0.6213   | 0.3832   | 0.6213 | 0.0    | 0.6207 | 0.6210    |
| 0.6826        | 7     | 2058 | 0.6676          | 0.5       | 44.2210       | 0.6213   | 0.3832   | 0.6213 | 0.0    | 0.6207 | 0.6210    |
| 0.6609        | 8.0   | 2352 | 0.6683          | 1.0       | 84.6792       | 0.6213   | 0.3832   | 0.6213 | 0.0    | 0.6207 | 0.6210    |
| 0.6732        | 9.0   | 2646 | 0.6649          | 1.0       | 95.4464       | 0.6213   | 0.3832   | 0.6213 | 0.0    | 0.6207 | 0.6210    |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.1