gemma7b-summarize-claude3sonnet-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: 2.7259
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 |
---|---|---|---|
18.539 | 0.9744 | 19 | 8.6238 |
11.8891 | 2.0 | 39 | 6.5199 |
2.3149 | 2.9744 | 58 | 3.2759 |
1.5266 | 4.0 | 78 | 2.8999 |
1.3332 | 4.9744 | 97 | 2.7966 |
1.2502 | 6.0 | 117 | 2.7460 |
1.2007 | 6.9744 | 136 | 2.7332 |
1.1904 | 8.0 | 156 | 2.7283 |
1.1866 | 8.9744 | 175 | 2.7323 |
1.1715 | 9.7436 | 190 | 2.7259 |
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-claude3sonnet-8k
Base model
google/gemma-7b