gemma7b-summarize-11k
This model is a fine-tuned version of google/gemma-7b on the chansung/merge_summarize_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 2.6219
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 |
---|---|---|---|
2.8367 | 0.9907 | 53 | 2.7327 |
1.0189 | 2.0 | 107 | 2.3246 |
0.8788 | 2.9907 | 160 | 2.2786 |
0.8104 | 4.0 | 214 | 2.2754 |
0.7626 | 4.9907 | 267 | 2.3205 |
0.6665 | 6.0 | 321 | 2.3903 |
0.6015 | 6.9907 | 374 | 2.4630 |
0.5699 | 8.0 | 428 | 2.5837 |
0.5017 | 8.9907 | 481 | 2.6300 |
0.4969 | 9.9065 | 530 | 2.6219 |
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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