gemma_summarizer_2
This model is a fine-tuned version of google/gemma-2-2b-it on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9349
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: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.3746 | 0.3999 | 630 | 2.0370 |
2.364 | 0.7997 | 1260 | 1.9673 |
2.2345 | 1.1996 | 1890 | 1.9486 |
1.2331 | 1.5995 | 2520 | 1.9388 |
1.1334 | 1.9994 | 3150 | 1.9349 |
Framework versions
- PEFT 0.11.1
- Transformers 4.44.0
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1
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