gemma2b-summarize-gemini1.5flash
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gemma2b-summarize-gemini1_5flash-4k
This model is a fine-tuned version of google/gemma-2b on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set:
- Loss: 2.5520
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.9598 | 1.0 | 7 | 3.0819 |
| 2.584 | 2.0 | 14 | 2.7799 |
| 1.8743 | 3.0 | 21 | 2.6390 |
| 1.6598 | 4.0 | 28 | 2.6231 |
| 1.4458 | 5.0 | 35 | 2.5861 |
| 1.3889 | 6.0 | 42 | 2.5646 |
| 1.3527 | 7.0 | 49 | 2.5569 |
| 1.2936 | 8.0 | 56 | 2.5532 |
| 1.2855 | 9.0 | 63 | 2.5514 |
| 1.2802 | 10.0 | 70 | 2.5520 |
Framework versions
- PEFT 0.11.1
- Transformers 4.40.1
- Pytorch 2.2.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Model tree for llama-duo/gemma2b-summarize-gemini1_5flash-4k
Base model
google/gemma-2b