---
license: other
library_name: peft
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- nthakur/miracl-raft-sft-instruct-v0.1
- nthakur/nomiracl-raft-sft-instruct-v0.1
- nthakur/miracl-en-x-raft-sft-instruct-v0.1
- nthakur/miracl-x-en-raft-sft-instruct-v0.1
base_model: meta-llama/Meta-Llama-3-8B-Instruct
model-index:
- name: Meta-Llama-3-8B-Instruct-miracl-mix-raft-sft-25th-apr-v1.0
  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. -->

# Meta-Llama-3-8B-Instruct-miracl-mix-raft-sft-25th-apr-v1.0

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 nthakur/miracl-raft-sft-instruct-v0.1, the nthakur/nomiracl-raft-sft-instruct-v0.1, the nthakur/miracl-en-x-raft-sft-instruct-v0.1 and the nthakur/miracl-x-en-raft-sft-instruct-v0.1 datasets.
It achieves the following results on the evaluation set:
- Loss: 1.3064

## 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: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4903        | 0.09  | 200  | 1.3961          |
| 1.465         | 0.18  | 400  | 1.3499          |
| 1.4193        | 0.28  | 600  | 1.3330          |
| 1.3593        | 0.37  | 800  | 1.3232          |
| 1.3552        | 0.46  | 1000 | 1.3166          |
| 1.3685        | 0.55  | 1200 | 1.3123          |
| 1.3487        | 0.64  | 1400 | 1.3094          |
| 1.3891        | 0.74  | 1600 | 1.3076          |
| 1.3858        | 0.83  | 1800 | 1.3067          |
| 1.3635        | 0.92  | 2000 | 1.3064          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2