---
library_name: transformers
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: combined_sft_mc_filtered
  results: []
datasets:
- hlillemark/mc_combined_sa_ma_dataset
---

<!-- 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. -->

# combined_sft_mc_filtered

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the identity and the data_mc_filtered datasets.
It achieves the following results on the evaluation set:
- Loss: 1.2652

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7445        | 0.7463 | 50   | 0.7196          |
| 0.576         | 1.4925 | 100  | 0.7831          |
| 0.3113        | 2.2388 | 150  | 0.8755          |
| 0.3723        | 2.9851 | 200  | 0.8511          |
| 0.2325        | 3.7313 | 250  | 0.8775          |
| 0.1831        | 4.4776 | 300  | 0.9325          |
| 0.107         | 5.2239 | 350  | 1.0493          |
| 0.0884        | 5.9701 | 400  | 0.9148          |
| 0.0442        | 6.7164 | 450  | 1.0387          |
| 0.0367        | 7.4627 | 500  | 1.1612          |
| 0.0111        | 8.2090 | 550  | 1.1844          |
| 0.016         | 8.9552 | 600  | 1.2519          |
| 0.0057        | 9.7015 | 650  | 1.2654          |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0