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--- |
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license: other |
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base_model: meta-llama/Meta-Llama-3-8B |
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tags: |
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- llama-factory |
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- full |
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- generated_from_trainer |
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model-index: |
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- name: C017_random_sample_llama3-8b-base_instruct_20240504_182259 |
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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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# C017_random_sample_llama3-8b-base_instruct_20240504_182259 |
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This model is a fine-tuned version of [./output/training_results/C017_random_sample_llama3-8b-base_pretrain_20240504_182259/](https://huggingface.co/./output/training_results/C017_random_sample_llama3-8b-base_pretrain_20240504_182259/) on the instructions_curated dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8518 |
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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: 1.5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: polynomial |
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- lr_scheduler_warmup_steps: 20 |
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- num_epochs: 4.0 |
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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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| 0.8222 | 0.4167 | 20 | 0.8593 | |
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| 0.8014 | 0.8333 | 40 | 0.8518 | |
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| 0.4422 | 1.25 | 60 | 0.8722 | |
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| 0.4551 | 1.6667 | 80 | 0.8555 | |
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| 0.3806 | 2.0833 | 100 | 0.8530 | |
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| 0.4011 | 2.5 | 120 | 0.8577 | |
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| 0.37 | 2.9167 | 140 | 0.8622 | |
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| 0.3626 | 3.3333 | 160 | 0.8659 | |
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| 0.3708 | 3.75 | 180 | 0.8687 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.3.0 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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