gemma7b-summarize-gemini1.5flash-80k
This model is a fine-tuned version of google/gemma-7b on the llama-duo/synth_summarize_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 3.0229
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: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 4
- 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 |
---|---|---|---|
0.8742 | 0.9982 | 280 | 2.1938 |
0.7213 | 2.0 | 561 | 2.1462 |
0.675 | 2.9982 | 841 | 2.1484 |
0.6439 | 4.0 | 1122 | 2.2149 |
0.569 | 4.9982 | 1402 | 2.3224 |
0.5317 | 6.0 | 1683 | 2.4839 |
0.472 | 6.9982 | 1963 | 2.6540 |
0.4306 | 8.0 | 2244 | 2.8791 |
0.4106 | 8.9982 | 2524 | 3.0011 |
0.4021 | 9.9822 | 2800 | 3.0229 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for llama-duo/gemma7b-summarize-gemini1.5flash-80k
Base model
google/gemma-7b