---
license: other
base_model: yandex/YandexGPT-5-Lite-8B-instruct
tags:
- generated_from_trainer
model-index:
- name: outputs
  results: []
library_name: peft
datasets:
- samedad/mem-and-russian-jokes-dataset
---

<!-- 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 [yandex/YandexGPT-5-Lite-8B-instruct](https://huggingface.co/yandex/YandexGPT-5-Lite-8B-instruct) on an 
[samedad/mem-and-russian-jokes-dataset](https://huggingface.co/datasets/samedad/mem-and-russian-jokes-dataset).
It achieves the following results on the evaluation set:
- Loss: 2.4964

## 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: QuantizationMethod.BITS_AND_BYTES
- _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
- load_in_4bit: True
- load_in_8bit: False
### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 6.3533        | 0.04  | 100  | 4.2878          |
| 3.3336        | 0.08  | 200  | 2.8855          |
| 2.8695        | 0.12  | 300  | 2.8085          |
| 2.7996        | 0.16  | 400  | 2.7477          |
| 2.7557        | 0.2   | 500  | 2.6723          |
| 2.6529        | 0.24  | 600  | 2.5928          |
| 2.6168        | 0.29  | 700  | 2.5523          |
| 2.585         | 0.33  | 800  | 2.5235          |
| 2.5576        | 0.37  | 900  | 2.5039          |
| 2.5305        | 0.41  | 1000 | 2.4964          |


### Framework versions

- PEFT 0.5.0
- Transformers 4.38.2
- Pytorch 2.6.0+cu124
- Datasets 4.1.1
- Tokenizers 0.15.2