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--- |
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base_model: meta-llama/Meta-Llama-3-8B-Instruct |
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datasets: |
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- nthakur/mirage-meta-llama-3-sft-instruct |
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library_name: peft |
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license: llama3 |
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tags: |
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- alignment-handbook |
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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: Meta-Llama-3-8B-Instruct-mirage-meta-llama-3-sft-instruct |
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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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# Meta-Llama-3-8B-Instruct-mirage-meta-llama-3-sft-instruct |
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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 the nthakur/mirage-meta-llama-3-sft-instruct dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2431 |
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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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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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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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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- total_eval_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: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.3403 | 0.0597 | 200 | 0.3074 | |
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| 0.3224 | 0.1195 | 400 | 0.2954 | |
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| 0.3055 | 0.1792 | 600 | 0.2886 | |
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| 0.2899 | 0.2389 | 800 | 0.2804 | |
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| 0.3116 | 0.2987 | 1000 | 0.2772 | |
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| 0.3101 | 0.3584 | 1200 | 0.2728 | |
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| 0.2913 | 0.4182 | 1400 | 0.2679 | |
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| 0.2765 | 0.4779 | 1600 | 0.2625 | |
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| 0.2697 | 0.5376 | 1800 | 0.2601 | |
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| 0.2759 | 0.5974 | 2000 | 0.2557 | |
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| 0.264 | 0.6571 | 2200 | 0.2524 | |
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| 0.2705 | 0.7168 | 2400 | 0.2490 | |
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| 0.2694 | 0.7766 | 2600 | 0.2466 | |
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| 0.2639 | 0.8363 | 2800 | 0.2450 | |
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| 0.2598 | 0.8961 | 3000 | 0.2435 | |
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| 0.2483 | 0.9558 | 3200 | 0.2432 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
