gemma2b-summarize-gemini1.5flash
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gemma2b-summarize-gemini1_5flash-256k
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: 2.5681
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: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- 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 |
|---|---|---|---|
| 1.0246 | 0.9976 | 207 | 2.4550 |
| 0.9556 | 2.0 | 415 | 2.4530 |
| 0.9114 | 2.9976 | 622 | 2.4641 |
| 0.8927 | 4.0 | 830 | 2.4882 |
| 0.8752 | 4.9976 | 1037 | 2.5081 |
| 0.8602 | 6.0 | 1245 | 2.5277 |
| 0.8464 | 6.9976 | 1452 | 2.5513 |
| 0.8353 | 8.0 | 1660 | 2.5615 |
| 0.8267 | 8.9976 | 1867 | 2.5674 |
| 0.8289 | 9.9976 | 2070 | 2.5681 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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