---
base_model: meta-llama/Meta-Llama-3-8B
datasets:
- arrow
library_name: peft
license: llama3
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: RoBERTa_LLama3_dependent_V1
  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. -->

# RoBERTa_LLama3_dependent_V1

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the arrow dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1905

## 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: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| No log        | 0.9927  | 68   | 4.2488          |
| No log        | 2.0     | 137  | 1.2150          |
| No log        | 2.9927  | 205  | 1.1606          |
| No log        | 4.0     | 274  | 1.1320          |
| No log        | 4.9927  | 342  | 1.1227          |
| No log        | 6.0     | 411  | 1.1144          |
| No log        | 6.9927  | 479  | 1.1148          |
| 1.9771        | 8.0     | 548  | 1.1420          |
| 1.9771        | 8.9927  | 616  | 1.1345          |
| 1.9771        | 10.0    | 685  | 1.2247          |
| 1.9771        | 10.9927 | 753  | 1.1905          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1