---
library_name: transformers
license: gemma
base_model: google/gemma-2b
tags:
- generated_from_trainer
metrics:
- accuracy
- rouge
model-index:
- name: 40efc318792ebd56a10f1612e2fce919
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 40efc318792ebd56a10f1612e2fce919

This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the nyu-mll/glue [mnli] dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4339
- Data Size: 0.5
- Epoch Runtime: 1125.5597
- Accuracy: 0.7509
- F1 Macro: 0.7503
- Rouge1: 0.7508
- Rouge2: 0.0
- Rougel: 0.7509
- Rougelsum: 0.7510

## 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     | 8.3050          | 0         | 14.1671       | 0.3243   | 0.1890   | 0.3246 | 0.0    | 0.3246 | 0.3244    |
| 4.2895        | 1     | 12271 | 3.0390          | 0.0078    | 30.4238       | 0.6819   | 0.6844   | 0.6818 | 0.0    | 0.6819 | 0.6819    |
| 2.5474        | 2     | 24542 | 2.6322          | 0.0156    | 51.3774       | 0.7443   | 0.7429   | 0.7440 | 0.0    | 0.7445 | 0.7447    |
| 2.5025        | 3     | 36813 | 2.2221          | 0.0312    | 90.2574       | 0.7816   | 0.7810   | 0.7816 | 0.0    | 0.7816 | 0.7815    |
| 2.5107        | 4     | 49084 | 2.4528          | 0.0625    | 160.5099      | 0.7479   | 0.7441   | 0.7473 | 0.0    | 0.7478 | 0.7478    |
| 2.42          | 5     | 61355 | 2.6393          | 0.125     | 294.8323      | 0.7353   | 0.7324   | 0.7353 | 0.0    | 0.7355 | 0.7354    |
| 2.5207        | 6     | 73626 | 2.5955          | 0.25      | 570.8636      | 0.7446   | 0.7434   | 0.7445 | 0.0    | 0.7446 | 0.7446    |
| 2.2561        | 7     | 85897 | 2.4339          | 0.5       | 1125.5597     | 0.7509   | 0.7503   | 0.7508 | 0.0    | 0.7509 | 0.7510    |


### Framework versions

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