End of training
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README.md
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---
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license: other
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base_model: yandex/YandexGPT-5-Lite-8B-instruct
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tags:
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- generated_from_trainer
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model-index:
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- name: outputs
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results: []
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library_name: peft
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# outputs
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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 unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.4964
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: QuantizationMethod.BITS_AND_BYTES
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- _load_in_8bit: False
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- _load_in_4bit: True
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: nf4
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- bnb_4bit_use_double_quant: True
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- bnb_4bit_compute_dtype: bfloat16
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- load_in_4bit: True
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- load_in_8bit: False
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 8
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 250
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- training_steps: 1000
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 6.3533 | 0.04 | 100 | 4.2878 |
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| 3.3336 | 0.08 | 200 | 2.8855 |
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| 2.8695 | 0.12 | 300 | 2.8085 |
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| 2.7996 | 0.16 | 400 | 2.7477 |
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| 2.7557 | 0.2 | 500 | 2.6723 |
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| 2.6529 | 0.24 | 600 | 2.5928 |
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| 2.6168 | 0.29 | 700 | 2.5523 |
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| 2.585 | 0.33 | 800 | 2.5235 |
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| 2.5576 | 0.37 | 900 | 2.5039 |
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| 2.5305 | 0.41 | 1000 | 2.4964 |
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### Framework versions
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- PEFT 0.5.0
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- Transformers 4.38.2
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- Pytorch 2.6.0+cu124
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- Datasets 4.1.1
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- Tokenizers 0.15.2
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