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output
This model is a fine-tuned version of decapoda-research/llama-7b-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Rouge2 Precision: 0.0762
- Rouge2 Recall: 0.0182
- Rouge2 Fmeasure: 0.029
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| No log | 1.0 | 63 | nan | 0.0762 | 0.0182 | 0.029 |
| No log | 2.0 | 126 | nan | 0.0762 | 0.0182 | 0.029 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2
