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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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- 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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- generator |
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model-index: |
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- name: gemma2b-summarize-gpt4o-64k |
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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-64k |
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This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.5990 |
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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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| 1.2959 | 1.0 | 146 | 2.5295 | |
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| 1.1524 | 2.0 | 292 | 2.4913 | |
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| 1.1138 | 3.0 | 438 | 2.4847 | |
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| 1.0703 | 4.0 | 584 | 2.4927 | |
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| 1.0423 | 5.0 | 730 | 2.5080 | |
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| 1.0322 | 6.0 | 876 | 2.5202 | |
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| 1.0113 | 7.0 | 1022 | 2.5385 | |
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| 0.9857 | 8.0 | 1168 | 2.5522 | |
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| 0.9865 | 9.0 | 1314 | 2.5657 | |
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| 0.9691 | 10.0 | 1460 | 2.5774 | |
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| 0.952 | 11.0 | 1606 | 2.5889 | |
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| 0.97 | 12.0 | 1752 | 2.5957 | |
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| 0.9514 | 13.0 | 1898 | 2.5988 | |
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| 0.9469 | 14.0 | 2044 | 2.5997 | |
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| 0.9469 | 15.0 | 2190 | 2.5990 | |
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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 |
