---
base_model: ybelkada/Mistral-7B-v0.1-bf16-sharded
tags:
- generated_from_trainer
model-index:
- name: my_tuned_json_data_model
  results: []
library_name: peft
---

<!-- 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. -->

# my_tuned_json_data_model

This model is a fine-tuned version of [ybelkada/Mistral-7B-v0.1-bf16-sharded](https://huggingface.co/ybelkada/Mistral-7B-v0.1-bf16-sharded) on the None dataset.

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: fp4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float32
### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- PEFT 0.4.0
- Transformers 4.35.0
- Pytorch 2.0.0+cu117
- Datasets 2.13.0
- Tokenizers 0.14.1