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--- |
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license: apache-2.0 |
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base_model: ondevicellm/tinyllama_moe |
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tags: |
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- alignment-handbook |
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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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- ondevicellm/SlimOrca |
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model-index: |
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- name: tinyllama_moe_sft_ultrachat-slimorca |
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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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# tinyllama_moe_sft_ultrachat-slimorca |
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This model is a fine-tuned version of [ondevicellm/tinyllama_moe](https://huggingface.co/ondevicellm/tinyllama_moe) on the HuggingFaceH4/ultrachat_200k and the ondevicellm/SlimOrca datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1526 |
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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: 16 |
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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: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 32 |
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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_steps: 120 |
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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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| 1.4601 | 0.05 | 100 | 1.3361 | |
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| 1.3324 | 0.1 | 200 | 1.2566 | |
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| 1.2946 | 0.14 | 300 | 1.2279 | |
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| 1.2767 | 0.19 | 400 | 1.2111 | |
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| 1.2298 | 0.24 | 500 | 1.1995 | |
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| 1.2247 | 0.29 | 600 | 1.1902 | |
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| 1.2208 | 0.34 | 700 | 1.1833 | |
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| 1.2375 | 0.39 | 800 | 1.1775 | |
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| 1.2038 | 0.43 | 900 | 1.1726 | |
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| 1.1926 | 0.48 | 1000 | 1.1683 | |
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| 1.1933 | 0.53 | 1100 | 1.1649 | |
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| 1.1893 | 0.58 | 1200 | 1.1618 | |
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| 1.2029 | 0.63 | 1300 | 1.1593 | |
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| 1.2201 | 0.68 | 1400 | 1.1572 | |
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| 1.1741 | 0.72 | 1500 | 1.1557 | |
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| 1.1813 | 0.77 | 1600 | 1.1545 | |
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| 1.1668 | 0.82 | 1700 | 1.1536 | |
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| 1.1495 | 0.87 | 1800 | 1.1530 | |
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| 1.1595 | 0.92 | 1900 | 1.1527 | |
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| 1.1607 | 0.97 | 2000 | 1.1526 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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