---
license: llama3
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B-Instruct
datasets:
- generator
model-index:
- name: MIDIGen_Llama3_8B-Instruct_finetuned_10epochs
  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. -->

# MIDIGen_Llama3_8B-Instruct_finetuned_10epochs

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 generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6254

## 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: 8
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.6577        | 0.9996 | 1386  | 0.6565          |
| 0.6373        | 2.0    | 2773  | 0.6403          |
| 0.6294        | 2.9996 | 4159  | 0.6344          |
| 0.6256        | 4.0    | 5546  | 0.6313          |
| 0.6257        | 4.9996 | 6932  | 0.6294          |
| 0.6255        | 6.0    | 8319  | 0.6280          |
| 0.6201        | 6.9996 | 9705  | 0.6271          |
| 0.6205        | 8.0    | 11092 | 0.6264          |
| 0.6205        | 8.9996 | 12478 | 0.6259          |
| 0.6252        | 9.9964 | 13860 | 0.6254          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.1.0
- Datasets 2.18.0
- Tokenizers 0.19.1