gemma7b-summarize-gpt4o-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: 2.6528
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 |
---|---|---|---|
19.7993 | 0.9818 | 27 | 7.7915 |
2.9592 | 2.0 | 55 | 3.8534 |
1.6171 | 2.9818 | 82 | 2.8793 |
1.3574 | 4.0 | 110 | 2.7211 |
1.2908 | 4.9818 | 137 | 2.6808 |
1.2355 | 6.0 | 165 | 2.6636 |
1.2095 | 6.9818 | 192 | 2.6539 |
1.1869 | 8.0 | 220 | 2.6529 |
1.1877 | 8.9818 | 247 | 2.6520 |
1.1898 | 9.8182 | 270 | 2.6528 |
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-gpt4o-16k
Base model
google/gemma-7b