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# mistral7b-sharded-finetune-bn22

This model is a fine-tuned version of [filipealmeida/Mistral-7B-Instruct-v0.1-sharded](https://huggingface.co/filipealmeida/Mistral-7B-Instruct-v0.1-sharded) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1132

## 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: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 2500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8338        | 0.16  | 100  | 1.4732          |
| 1.3163        | 0.33  | 200  | 1.2741          |
| 1.2292        | 0.49  | 300  | 1.2399          |
| 1.1665        | 0.65  | 400  | 1.2146          |
| 1.1597        | 0.82  | 500  | 1.1913          |
| 1.1025        | 0.98  | 600  | 1.1699          |
| 1.03          | 1.14  | 700  | 1.1546          |
| 1.0461        | 1.31  | 800  | 1.1491          |
| 1.0149        | 1.47  | 900  | 1.1334          |
| 0.9989        | 1.63  | 1000 | 1.1270          |
| 1.0385        | 1.79  | 1100 | 1.1184          |
| 1.0051        | 1.96  | 1200 | 1.1102          |
| 0.9365        | 2.12  | 1300 | 1.1210          |
| 0.8931        | 2.28  | 1400 | 1.1105          |
| 0.9094        | 2.45  | 1500 | 1.1095          |
| 0.8989        | 2.61  | 1600 | 1.1079          |
| 0.9027        | 2.77  | 1700 | 1.1043          |
| 0.9007        | 2.94  | 1800 | 1.1010          |
| 0.8666        | 3.1   | 1900 | 1.1111          |
| 0.8259        | 3.26  | 2000 | 1.1128          |
| 0.8288        | 3.43  | 2100 | 1.1153          |
| 0.8223        | 3.59  | 2200 | 1.1133          |
| 0.7891        | 3.75  | 2300 | 1.1132          |


### Framework versions

- PEFT 0.7.0
- Transformers 4.36.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
{"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "filipealmeida/Mistral-7B-Instruct-v0.1-sharded", "model-index": [{"name": "mistral7b-sharded-finetune-bn22", "results": []}]}
peft tensorboard safetensors generated_from_trainer base_model:filipealmeida/Mistral-7B-Instruct-v0.1-sharded license:apache-2.0 region:us