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# mistral7b-sharded-finetune-v02-11-12-23

This model is a fine-tuned version of [filipealmeida/Mistral-7B-v0.1-sharded](https://huggingface.co/filipealmeida/Mistral-7B-v0.1-sharded) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6195

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.1478        | 0.07  | 100  | 0.9744          |
| 0.8538        | 0.14  | 200  | 0.7786          |
| 0.768         | 0.21  | 300  | 0.7456          |
| 0.7403        | 0.28  | 400  | 0.7313          |
| 0.7314        | 0.35  | 500  | 0.7118          |
| 0.7072        | 0.42  | 600  | 0.6991          |
| 0.7005        | 0.5   | 700  | 0.6861          |
| 0.6879        | 0.57  | 800  | 0.6788          |
| 0.6725        | 0.64  | 900  | 0.6727          |
| 0.6832        | 0.71  | 1000 | 0.6644          |
| 0.6745        | 0.78  | 1100 | 0.6588          |
| 0.6745        | 0.85  | 1200 | 0.6525          |
| 0.6651        | 0.92  | 1300 | 0.6490          |
| 0.6377        | 0.99  | 1400 | 0.6436          |
| 0.5864        | 1.06  | 1500 | 0.6404          |
| 0.5961        | 1.13  | 1600 | 0.6365          |
| 0.6147        | 1.2   | 1700 | 0.6303          |
| 0.6157        | 1.27  | 1800 | 0.6263          |
| 0.5917        | 1.34  | 1900 | 0.6246          |
| 0.6118        | 1.42  | 2000 | 0.6232          |
| 0.6033        | 1.49  | 2100 | 0.6215          |
| 0.5718        | 1.56  | 2200 | 0.6200          |
| 0.6074        | 1.63  | 2300 | 0.6197          |
| 0.5735        | 1.7   | 2400 | 0.6196          |
| 0.5893        | 1.77  | 2500 | 0.6195          |


### 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-v0.1-sharded", "model-index": [{"name": "mistral7b-sharded-finetune-v02-11-12-23", "results": []}]}
peft safetensors llama generated_from_trainer base_model:filipealmeida/Mistral-7B-v0.1-sharded license:apache-2.0 region:us