llama38binstruct_summarize
This model is a fine-tuned version of NousResearch/Meta-Llama-3-8B-Instruct on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 1.4391
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: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 0.03
- training_steps: 100
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.4009 | 1.3889 | 25 | 1.0738 |
| 0.4554 | 2.7778 | 50 | 1.2629 |
| 0.2384 | 4.1667 | 75 | 1.3364 |
| 0.0555 | 5.5556 | 100 | 1.4391 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for dwb2023/llama38binstruct_summarize
Base model
NousResearch/Meta-Llama-3-8B-Instruct