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---
library_name: transformers
license: other
base_model: meta-llama/Llama-3.2-3B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: t1_25k_v2_tag5
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. -->
# t1_25k_v2_tag5
This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on the t1_25k_v2_tag5 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3038
## 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-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.3537 | 0.0833 | 100 | 0.4035 |
| 0.3871 | 0.1667 | 200 | 0.3606 |
| 0.321 | 0.25 | 300 | 0.3481 |
| 0.3558 | 0.3333 | 400 | 0.3372 |
| 0.3775 | 0.4167 | 500 | 0.3321 |
| 0.3283 | 0.5 | 600 | 0.3225 |
| 0.3371 | 0.5833 | 700 | 0.3186 |
| 0.3005 | 0.6667 | 800 | 0.3113 |
| 0.3223 | 0.75 | 900 | 0.3080 |
| 0.3302 | 0.8333 | 1000 | 0.3047 |
| 0.2852 | 0.9167 | 1100 | 0.3041 |
| 0.2686 | 1.0 | 1200 | 0.3038 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.6.0+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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