gemma7b-summarize
This model is a fine-tuned version of google/gemma-7b on the llama-duo/coverage_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 3.3615
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 |
|---|---|---|---|
| 17.2572 | 1.0 | 5 | 11.2704 |
| 10.1138 | 2.0 | 10 | 7.8912 |
| 7.7504 | 3.0 | 15 | 7.1928 |
| 7.0505 | 4.0 | 20 | 6.8083 |
| 6.6144 | 5.0 | 25 | 6.4041 |
| 6.066 | 6.0 | 30 | 5.7488 |
| 5.1349 | 7.0 | 35 | 4.6655 |
| 3.9891 | 8.0 | 40 | 3.7537 |
| 3.293 | 9.0 | 45 | 3.3924 |
| 3.098 | 10.0 | 50 | 3.3615 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
google/gemma-7b