---
library_name: transformers
license: apache-2.0
base_model: albert/albert-xxlarge-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- rouge
model-index:
- name: 9984b730e8070704466d394c09272b8a
  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. -->

# 9984b730e8070704466d394c09272b8a

This model is a fine-tuned version of [albert/albert-xxlarge-v2](https://huggingface.co/albert/albert-xxlarge-v2) on the nyu-mll/glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5860
- Data Size: 1.0
- Epoch Runtime: 17.2628
- Accuracy: 0.8086
- F1 Macro: 0.7769
- Rouge1: 0.8096
- Rouge2: 0.0
- Rougel: 0.8086
- Rougelsum: 0.8086

## 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    | 0.6812          | 0         | 1.0866        | 0.6377   | 0.5163   | 0.6377 | 0.0    | 0.6377 | 0.6387    |
| No log        | 1     | 267  | 0.6836          | 0.0078    | 1.7720        | 0.5205   | 0.4498   | 0.5205 | 0.0    | 0.5205 | 0.5205    |
| No log        | 2     | 534  | 0.6158          | 0.0156    | 1.7797        | 0.6885   | 0.4108   | 0.6895 | 0.0    | 0.6885 | 0.6885    |
| No log        | 3     | 801  | 0.6296          | 0.0312    | 2.1033        | 0.6611   | 0.6026   | 0.6611 | 0.0    | 0.6611 | 0.6616    |
| No log        | 4     | 1068 | 0.5519          | 0.0625    | 2.4921        | 0.7021   | 0.4733   | 0.7031 | 0.0    | 0.7031 | 0.7012    |
| 0.0336        | 5     | 1335 | 0.6704          | 0.125     | 3.4358        | 0.7236   | 0.5739   | 0.7236 | 0.0    | 0.7236 | 0.7231    |
| 0.4919        | 6     | 1602 | 0.4829          | 0.25      | 5.3458        | 0.7871   | 0.7350   | 0.7861 | 0.0    | 0.7861 | 0.7871    |
| 0.4105        | 7     | 1869 | 0.4351          | 0.5       | 9.3113        | 0.8174   | 0.7753   | 0.8174 | 0.0    | 0.8174 | 0.8174    |
| 0.3572        | 8.0   | 2136 | 0.4500          | 1.0       | 17.4779       | 0.8164   | 0.7780   | 0.8164 | 0.0    | 0.8164 | 0.8164    |
| 0.2837        | 9.0   | 2403 | 0.4056          | 1.0       | 17.1662       | 0.8320   | 0.7872   | 0.8320 | 0.0    | 0.8320 | 0.8320    |
| 0.2434        | 10.0  | 2670 | 0.4391          | 1.0       | 17.1180       | 0.8320   | 0.7996   | 0.8320 | 0.0    | 0.8320 | 0.8320    |
| 0.1855        | 11.0  | 2937 | 0.4628          | 1.0       | 17.0875       | 0.8232   | 0.7965   | 0.8232 | 0.0    | 0.8232 | 0.8223    |
| 0.1922        | 12.0  | 3204 | 0.5114          | 1.0       | 17.1420       | 0.8057   | 0.7759   | 0.8057 | 0.0    | 0.8047 | 0.8066    |
| 0.1294        | 13.0  | 3471 | 0.5860          | 1.0       | 17.2628       | 0.8086   | 0.7769   | 0.8096 | 0.0    | 0.8086 | 0.8086    |


### Framework versions

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