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--- |
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base_model: meta-llama/Meta-Llama-3-8B-Instruct |
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library_name: peft |
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license: llama3 |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: experiments |
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results: [] |
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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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# experiments |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co./meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4332 |
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## Model description |
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``` |
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MODEL_NAME = "/content/blackhole33/llama-5000-sample-peft" |
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quantization_config = BitsAndBytesConfig( |
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load_in_4bit=True, bnb_4bit_quant_type="nf4", bnb_4bit_compute_dtype=torch.bfloat16 |
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) |
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tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, use_fast=True) |
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model = AutoModelForCausalLM.from_pretrained( |
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MODEL_NAME, quantization_config=quantization_config, device_map="auto" |
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) |
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``` |
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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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### 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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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: constant |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1 |
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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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| 1.3475 | 0.2 | 100 | 1.5142 | |
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| 1.4979 | 0.4 | 200 | 1.4703 | |
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| 1.4307 | 0.6 | 300 | 1.4510 | |
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| 1.3795 | 0.8 | 400 | 1.4434 | |
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| 1.3847 | 1.0 | 500 | 1.4332 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.1 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
