---
base_model: vilsonrodrigues/falcon-7b-instruct-sharded
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: falcon7binstruct_fine_tunning_PPF_english_conversations_fake
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/rafael-torrestimal-Personal/huggingface/runs/q4cyw2ji)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/rafael-torrestimal-Personal/huggingface/runs/q4cyw2ji)
# falcon7binstruct_fine_tunning_PPF_english_conversations_fake

This model is a fine-tuned version of [vilsonrodrigues/falcon-7b-instruct-sharded](https://huggingface.co/vilsonrodrigues/falcon-7b-instruct-sharded) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4691

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7389        | 0.0667 | 10   | 0.6081          |
| 0.56          | 0.1333 | 20   | 0.5264          |
| 0.5216        | 0.2    | 30   | 0.4919          |
| 0.4881        | 0.2667 | 40   | 0.4722          |
| 0.4646        | 0.3333 | 50   | 0.4691          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.43.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1