tensorboard safetensors trl sft generated_from_trainer base_model:ybelkada/falcon-7b-sharded-bf16 region:us
---
base_model: ybelkada/falcon-7b-sharded-bf16
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: unsloth-test
  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. -->

# unsloth-test

This model is a fine-tuned version of [ybelkada/falcon-7b-sharded-bf16](https://huggingface.co/ybelkada/falcon-7b-sharded-bf16) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1783

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 3407
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.9064        | 0.03  | 10   | 2.3285          |
| 1.7147        | 0.05  | 20   | 2.1141          |
| 1.9815        | 0.08  | 30   | 1.9912          |
| 1.6473        | 0.11  | 40   | 1.9045          |
| 1.8572        | 0.14  | 50   | 1.8468          |
| 1.4015        | 0.16  | 60   | 1.7899          |
| 1.3057        | 0.19  | 70   | 1.7523          |
| 1.4202        | 0.22  | 80   | 1.7084          |
| 1.2665        | 0.24  | 90   | 1.6817          |
| 1.1922        | 0.27  | 100  | 1.6452          |
| 1.0946        | 0.3   | 110  | 1.6227          |
| 1.1268        | 0.33  | 120  | 1.6033          |
| 1.4784        | 0.35  | 130  | 1.5873          |
| 1.2049        | 0.38  | 140  | 1.5733          |
| 1.1141        | 0.41  | 150  | 1.5400          |
| 1.2119        | 0.43  | 160  | 1.5317          |
| 1.5383        | 0.46  | 170  | 1.5195          |
| 1.308         | 0.49  | 180  | 1.5100          |
| 1.6075        | 0.52  | 190  | 1.4901          |
| 1.4443        | 0.54  | 200  | 1.4942          |
| 1.4493        | 0.57  | 210  | 1.4685          |
| 0.8844        | 0.6   | 220  | 1.4677          |
| 1.2082        | 0.62  | 230  | 1.4518          |
| 1.1994        | 0.65  | 240  | 1.4380          |
| 0.7472        | 0.68  | 250  | 1.4300          |
| 1.0516        | 0.71  | 260  | 1.4183          |
| 0.9373        | 0.73  | 270  | 1.4178          |
| 1.1221        | 0.76  | 280  | 1.4010          |
| 1.0978        | 0.79  | 290  | 1.3931          |
| 1.1696        | 0.82  | 300  | 1.3853          |
| 0.8722        | 0.84  | 310  | 1.3673          |
| 0.8707        | 0.87  | 320  | 1.3583          |
| 0.9933        | 0.9   | 330  | 1.3480          |
| 1.0988        | 0.92  | 340  | 1.3450          |
| 0.9995        | 0.95  | 350  | 1.3399          |
| 0.9277        | 0.98  | 360  | 1.3414          |
| 0.7538        | 1.01  | 370  | 1.3260          |
| 0.7933        | 1.03  | 380  | 1.3152          |
| 0.9362        | 1.06  | 390  | 1.3101          |
| 0.8345        | 1.09  | 400  | 1.3023          |
| 0.9271        | 1.11  | 410  | 1.3044          |
| 1.0953        | 1.14  | 420  | 1.3081          |
| 1.0863        | 1.17  | 430  | 1.2927          |
| 0.8999        | 1.2   | 440  | 1.2951          |
| 1.0146        | 1.22  | 450  | 1.2842          |
| 0.6808        | 1.25  | 460  | 1.2784          |
| 0.8005        | 1.28  | 470  | 1.2713          |
| 0.746         | 1.3   | 480  | 1.2642          |
| 0.9976        | 1.33  | 490  | 1.2661          |
| 0.7508        | 1.36  | 500  | 1.2539          |
| 0.8439        | 1.39  | 510  | 1.2462          |
| 0.7671        | 1.41  | 520  | 1.2465          |
| 0.7547        | 1.44  | 530  | 1.2421          |
| 0.6882        | 1.47  | 540  | 1.2426          |
| 1.0217        | 1.49  | 550  | 1.2381          |
| 0.6518        | 1.52  | 560  | 1.2324          |
| 0.9974        | 1.55  | 570  | 1.2324          |
| 0.7781        | 1.58  | 580  | 1.2292          |
| 0.7264        | 1.6   | 590  | 1.2296          |
| 0.9346        | 1.63  | 600  | 1.2255          |
| 0.7346        | 1.66  | 610  | 1.2223          |
| 0.9378        | 1.68  | 620  | 1.2164          |
| 0.8924        | 1.71  | 630  | 1.2176          |
| 1.2544        | 1.74  | 640  | 1.2157          |
| 0.7287        | 1.77  | 650  | 1.2155          |
| 0.7783        | 1.79  | 660  | 1.2069          |
| 0.8022        | 1.82  | 670  | 1.2049          |
| 0.9351        | 1.85  | 680  | 1.1969          |
| 0.891         | 1.88  | 690  | 1.2017          |
| 0.9973        | 1.9   | 700  | 1.2013          |
| 0.7192        | 1.93  | 710  | 1.2034          |
| 0.6488        | 1.96  | 720  | 1.1970          |
| 0.6643        | 1.98  | 730  | 1.1986          |
| 0.9502        | 2.01  | 740  | 1.1922          |
| 0.7626        | 2.04  | 750  | 1.1951          |
| 0.7211        | 2.07  | 760  | 1.1904          |
| 0.6385        | 2.09  | 770  | 1.1911          |
| 0.7917        | 2.12  | 780  | 1.1898          |
| 0.7153        | 2.15  | 790  | 1.1914          |
| 0.808         | 2.17  | 800  | 1.1869          |
| 0.6567        | 2.2   | 810  | 1.1870          |
| 0.5624        | 2.23  | 820  | 1.1909          |
| 0.7756        | 2.26  | 830  | 1.1869          |
| 0.8657        | 2.28  | 840  | 1.1864          |
| 1.0908        | 2.31  | 850  | 1.1866          |
| 0.9891        | 2.34  | 860  | 1.1835          |
| 0.7495        | 2.36  | 870  | 1.1784          |
| 0.7918        | 2.39  | 880  | 1.1809          |
| 0.8408        | 2.42  | 890  | 1.1808          |
| 0.9415        | 2.45  | 900  | 1.1807          |
| 0.8744        | 2.47  | 910  | 1.1793          |
| 0.6232        | 2.5   | 920  | 1.1784          |
| 0.7813        | 2.53  | 930  | 1.1797          |
| 0.959         | 2.55  | 940  | 1.1795          |
| 0.8303        | 2.58  | 950  | 1.1796          |
| 0.7675        | 2.61  | 960  | 1.1790          |
| 0.9452        | 2.64  | 970  | 1.1784          |
| 0.7509        | 2.66  | 980  | 1.1783          |
| 0.5698        | 2.69  | 990  | 1.1784          |
| 0.8727        | 2.72  | 1000 | 1.1783          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
