gemma7b-summarize-gemini1_5flash-8k
This model is a fine-tuned version of google/gemma-7b on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set:
- Loss: 2.8396
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: 4
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- 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 |
---|---|---|---|
31.311 | 0.9630 | 13 | 11.0230 |
19.0651 | 2.0 | 27 | 7.4342 |
11.34 | 2.9630 | 40 | 6.8118 |
3.0136 | 4.0 | 54 | 3.6308 |
1.7786 | 4.9630 | 67 | 3.0973 |
1.4865 | 6.0 | 81 | 2.9241 |
1.4036 | 6.9630 | 94 | 2.8645 |
1.3424 | 8.0 | 108 | 2.8510 |
1.3298 | 8.9630 | 121 | 2.8410 |
1.3245 | 9.6296 | 130 | 2.8396 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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Model tree for llama-duo/gemma7b-summarize-gemini1_5flash-8k
Base model
google/gemma-7b