gemma7b-summarize-claude3sonnet-16k
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: 2.6068
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 |
---|---|---|---|
13.7073 | 1.0 | 38 | 7.1377 |
1.6173 | 2.0 | 76 | 2.9757 |
1.2585 | 3.0 | 114 | 2.7226 |
1.1493 | 4.0 | 152 | 2.6312 |
1.0934 | 5.0 | 190 | 2.6200 |
1.0587 | 6.0 | 228 | 2.6020 |
1.0289 | 7.0 | 266 | 2.5996 |
1.0197 | 8.0 | 304 | 2.6022 |
1.0221 | 9.0 | 342 | 2.6059 |
1.0175 | 10.0 | 380 | 2.6068 |
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-16k
Base model
google/gemma-7b