---
library_name: transformers
license: gemma
base_model: google/gemma-2b
tags:
- generated_from_trainer
metrics:
- accuracy
- rouge
model-index:
- name: fc1c884c2af6bdedbfe7ea88893ba8e9
  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. -->

# fc1c884c2af6bdedbfe7ea88893ba8e9

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the nyu-mll/glue [mrpc] dataset.
It achieves the following results on the evaluation set:
- Loss: 7.6709
- Data Size: 1.0
- Epoch Runtime: 28.3061
- Accuracy: 0.7783
- F1 Macro: 0.7153
- Rouge1: 0.7783
- Rouge2: 0.0
- Rougel: 0.7777
- Rougelsum: 0.7783

## 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    | 2.7643          | 0         | 3.3412        | 0.6126   | 0.5522   | 0.6132 | 0.0    | 0.6126 | 0.6120    |
| No log        | 1     | 114  | 5.1579          | 0.0078    | 3.9321        | 0.6592   | 0.4637   | 0.6592 | 0.0    | 0.6586 | 0.6592    |
| No log        | 2     | 228  | 3.6322          | 0.0156    | 8.1285        | 0.6692   | 0.4777   | 0.6692 | 0.0    | 0.6692 | 0.6692    |
| No log        | 3     | 342  | 4.6142          | 0.0312    | 12.6551       | 0.6663   | 0.4032   | 0.6669 | 0.0    | 0.6660 | 0.6657    |
| 0.1148        | 4     | 456  | 3.1486          | 0.0625    | 15.1708       | 0.7028   | 0.5735   | 0.7028 | 0.0    | 0.7019 | 0.7034    |
| 0.1148        | 5     | 570  | 2.5100          | 0.125     | 19.7567       | 0.6686   | 0.4762   | 0.6692 | 0.0    | 0.6680 | 0.6686    |
| 0.1148        | 6     | 684  | 3.2711          | 0.25      | 21.6517       | 0.4593   | 0.4429   | 0.4587 | 0.0    | 0.4593 | 0.4599    |
| 0.6767        | 7     | 798  | 2.1242          | 0.5       | 28.5181       | 0.7529   | 0.7261   | 0.7524 | 0.0    | 0.7524 | 0.7535    |
| 1.7658        | 8.0   | 912  | 1.9603          | 1.0       | 41.3399       | 0.7647   | 0.6914   | 0.7647 | 0.0    | 0.7642 | 0.7647    |
| 1.0099        | 9.0   | 1026 | 3.0099          | 1.0       | 41.6100       | 0.7606   | 0.7253   | 0.7606 | 0.0    | 0.7606 | 0.7612    |
| 1.0121        | 10.0  | 1140 | 3.4193          | 1.0       | 41.8100       | 0.7677   | 0.7235   | 0.7677 | 0.0    | 0.7671 | 0.7671    |
| 0.6692        | 11.0  | 1254 | 3.5542          | 1.0       | 41.4199       | 0.7795   | 0.7605   | 0.7789 | 0.0    | 0.7789 | 0.7795    |
| 0.5981        | 12.0  | 1368 | 7.6709          | 1.0       | 28.3061       | 0.7783   | 0.7153   | 0.7783 | 0.0    | 0.7777 | 0.7783    |


### Framework versions

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