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--- |
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license: gemma |
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library_name: peft |
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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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base_model: google/gemma-2b |
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datasets: |
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- llama-duo/synth_summarize_dataset_dedup |
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model-index: |
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- name: gemma2b-summarize-gpt4o-128k |
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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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# gemma2b-summarize-gpt4o-128k |
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This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the llama-duo/synth_summarize_dataset_dedup dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.5233 |
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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: 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: 3 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 48 |
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- total_eval_batch_size: 24 |
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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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.2085 | 1.0 | 293 | 2.4863 | |
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| 1.1135 | 2.0 | 586 | 2.4516 | |
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| 1.0715 | 3.0 | 879 | 2.4473 | |
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| 1.0471 | 4.0 | 1172 | 2.4524 | |
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| 1.0357 | 5.0 | 1465 | 2.4685 | |
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| 0.993 | 6.0 | 1758 | 2.4703 | |
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| 0.9941 | 7.0 | 2051 | 2.4906 | |
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| 0.9844 | 8.0 | 2344 | 2.4896 | |
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| 0.9779 | 9.0 | 2637 | 2.5025 | |
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| 0.9639 | 10.0 | 2930 | 2.5126 | |
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| 0.952 | 11.0 | 3223 | 2.5192 | |
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| 0.9505 | 12.0 | 3516 | 2.5205 | |
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| 0.9442 | 13.0 | 3809 | 2.5223 | |
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| 0.9469 | 14.0 | 4102 | 2.5227 | |
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| 0.9444 | 15.0 | 4395 | 2.5233 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
