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--- |
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library_name: transformers |
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license: llama3.1 |
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base_model: meta-llama/Llama-3.1-8B |
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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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- trl |
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- sft |
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- generated_from_trainer |
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datasets: |
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- HuggingFaceH4/ultrachat_200k |
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model-index: |
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- name: zephyr-8b-sft-full |
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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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# zephyr-8b-sft-full |
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This model is a fine-tuned version of [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) on the HuggingFaceH4/ultrachat_200k dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0747 |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 16 |
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- total_train_batch_size: 128 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.103 | 0.1052 | 100 | 1.0989 | |
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| 1.0867 | 0.2103 | 200 | 1.0966 | |
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| 1.111 | 0.3155 | 300 | 1.1012 | |
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| 1.0974 | 0.4206 | 400 | 1.0966 | |
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| 1.0898 | 0.5258 | 500 | 1.0920 | |
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| 1.0749 | 0.6309 | 600 | 1.0876 | |
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| 1.0847 | 0.7361 | 700 | 1.0831 | |
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| 1.0749 | 0.8412 | 800 | 1.0778 | |
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| 1.055 | 0.9464 | 900 | 1.0720 | |
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| 0.9184 | 1.0515 | 1000 | 1.0817 | |
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| 0.8955 | 1.1567 | 1100 | 1.0779 | |
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| 0.914 | 1.2618 | 1200 | 1.0758 | |
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| 0.9098 | 1.3670 | 1300 | 1.0698 | |
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| 0.9126 | 1.4721 | 1400 | 1.0667 | |
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| 0.9032 | 1.5773 | 1500 | 1.0604 | |
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| 0.8882 | 1.6824 | 1600 | 1.0546 | |
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| 0.8847 | 1.7876 | 1700 | 1.0490 | |
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| 0.8831 | 1.8927 | 1800 | 1.0455 | |
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| 0.8781 | 1.9979 | 1900 | 1.0413 | |
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| 0.7197 | 2.1030 | 2000 | 1.0822 | |
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| 0.7137 | 2.2082 | 2100 | 1.0841 | |
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| 0.7115 | 2.3134 | 2200 | 1.0800 | |
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| 0.7178 | 2.4185 | 2300 | 1.0789 | |
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| 0.7063 | 2.5237 | 2400 | 1.0777 | |
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| 0.6964 | 2.6288 | 2500 | 1.0755 | |
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| 0.7121 | 2.7340 | 2600 | 1.0742 | |
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| 0.7049 | 2.8391 | 2700 | 1.0748 | |
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| 0.7024 | 2.9443 | 2800 | 1.0747 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.2.2+rocm5.7 |
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- Datasets 3.2.0 |
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- Tokenizers 0.20.3 |
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