---
library_name: peft
license: llama2
base_model: Yellow-AI-NLP/komodo-7b-base
tags:
- trl
- sft
- generated_from_trainer
datasets:
- id_nergrit_corpus
model-index:
- name: result
  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. -->

# result

This model is a fine-tuned version of [Yellow-AI-NLP/komodo-7b-base](https://huggingface.co/Yellow-AI-NLP/komodo-7b-base) on the id_nergrit_corpus dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0598
- eval_runtime: 429.4851
- eval_samples_per_second: 1.469
- eval_steps_per_second: 0.368
- epoch: 0.8265
- step: 162

## 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: float16
- bnb_4bit_quant_storage: uint8
- load_in_4bit: True
- load_in_8bit: False
### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
- mixed_precision_training: Native AMP

### Framework versions

- PEFT 0.4.0
- Transformers 4.44.1
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1