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---
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: []
---
<!-- 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. -->
[<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 |