---
tags:
- generated_from_trainer
model-index:
- name: falcon-7b-ft-self_instruct
  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. -->

# falcon-7b-ft-self_instruct

This model is a fine-tuned version of [ybelkada/falcon-7b-sharded-bf16](https://huggingface.co/ybelkada/falcon-7b-sharded-bf16) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7991

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9935        | 0.09  | 100  | 1.0028          |
| 1.0094        | 0.17  | 200  | 0.9614          |
| 0.8897        | 0.26  | 300  | 0.9396          |
| 0.9435        | 0.34  | 400  | 0.9260          |
| 0.9618        | 0.43  | 500  | 0.9146          |
| 0.8103        | 0.52  | 600  | 0.9035          |
| 0.8889        | 0.6   | 700  | 0.8966          |
| 0.8915        | 0.69  | 800  | 0.8884          |
| 0.8814        | 0.77  | 900  | 0.8833          |
| 0.9207        | 0.86  | 1000 | 0.8742          |
| 0.8284        | 0.95  | 1100 | 0.8693          |
| 0.8283        | 1.03  | 1200 | 0.8682          |
| 0.7445        | 1.12  | 1300 | 0.8659          |
| 0.8238        | 1.2   | 1400 | 0.8640          |
| 0.7448        | 1.29  | 1500 | 0.8537          |
| 0.7866        | 1.38  | 1600 | 0.8534          |
| 0.7224        | 1.46  | 1700 | 0.8480          |
| 0.7235        | 1.55  | 1800 | 0.8399          |
| 0.7936        | 1.64  | 1900 | 0.8385          |
| 0.7487        | 1.72  | 2000 | 0.8337          |
| 0.7842        | 1.81  | 2100 | 0.8284          |
| 0.7198        | 1.89  | 2200 | 0.8251          |
| 0.7507        | 1.98  | 2300 | 0.8188          |
| 0.622         | 2.07  | 2400 | 0.8353          |
| 0.6592        | 2.15  | 2500 | 0.8358          |
| 0.6043        | 2.24  | 2600 | 0.8330          |
| 0.7259        | 2.32  | 2700 | 0.8324          |
| 0.6388        | 2.41  | 2800 | 0.8290          |
| 0.7284        | 2.5   | 2900 | 0.8224          |
| 0.6166        | 2.58  | 3000 | 0.8202          |
| 0.6132        | 2.67  | 3100 | 0.8122          |
| 0.6323        | 2.75  | 3200 | 0.8094          |
| 0.6686        | 2.84  | 3300 | 0.8034          |
| 0.6457        | 2.93  | 3400 | 0.7991          |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3