---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: alexsherstinsky/Mistral-7B-v0.1-sharded
model-index:
- name: outputs
  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. -->

# outputs

This model is a fine-tuned version of [alexsherstinsky/Mistral-7B-v0.1-sharded](https://huggingface.co/alexsherstinsky/Mistral-7B-v0.1-sharded) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000

## 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-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.0235        | 0.07  | 100  | 0.0231          |
| 0.0187        | 0.15  | 200  | 0.0185          |
| 0.0141        | 0.22  | 300  | 0.0140          |
| 0.0085        | 0.29  | 400  | 0.0083          |
| 0.0015        | 0.37  | 500  | 0.0014          |
| 0.0007        | 0.44  | 600  | 0.0003          |
| 0.0005        | 0.52  | 700  | 0.0001          |
| 0.0004        | 0.59  | 800  | 0.0001          |
| 0.0003        | 0.66  | 900  | 0.0001          |
| 0.0001        | 0.74  | 1000 | 0.0000          |
| 0.0001        | 0.81  | 1100 | 0.0000          |
| 0.0           | 0.88  | 1200 | 0.0000          |
| 0.0001        | 0.96  | 1300 | 0.0000          |


### Framework versions

- PEFT 0.8.2
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1