---
library_name: transformers
license: llama3.2
base_model: meta-llama/Llama-3.2-1B-Instruct
tags:
- generated_from_trainer
metrics:
- accuracy
- rouge
model-index:
- name: 7d89ba274ad8c57c19fc44dd42b35f96
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 7d89ba274ad8c57c19fc44dd42b35f96

This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) on the google/boolq dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6552
- Data Size: 0.5
- Epoch Runtime: 31.5298
- 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    | 11.2514         | 0         | 5.5727        | 0.3808   | 0.2831   | 0.3808 | 0.0    | 0.3811 | 0.3811    |
| No log        | 1     | 294  | 21.3760         | 0.0078    | 5.8753        | 0.3909   | 0.3194   | 0.3915 | 0.0    | 0.3915 | 0.3912    |
| No log        | 2     | 588  | 6.8944          | 0.0156    | 6.9392        | 0.3787   | 0.2747   | 0.3787 | 0.0    | 0.3793 | 0.3790    |
| No log        | 3     | 882  | 2.6485          | 0.0312    | 8.7283        | 0.6219   | 0.3850   | 0.6219 | 0.0    | 0.6215 | 0.6219    |
| 0.2746        | 4     | 1176 | 2.6519          | 0.0625    | 10.2106       | 0.6192   | 0.4498   | 0.6192 | 0.0    | 0.6192 | 0.6189    |
| 0.2675        | 5     | 1470 | 2.7448          | 0.125     | 14.0979       | 0.6213   | 0.3832   | 0.6213 | 0.0    | 0.6207 | 0.6210    |
| 0.4191        | 6     | 1764 | 2.8210          | 0.25      | 20.4202       | 0.4020   | 0.3329   | 0.4017 | 0.0    | 0.4029 | 0.4020    |
| 2.711         | 7     | 2058 | 2.6552          | 0.5       | 31.5298       | 0.6213   | 0.3832   | 0.6213 | 0.0    | 0.6207 | 0.6210    |


### Framework versions

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