Text Generation --- Completion Generation Models
Collection
Models predicts the next word given a bunch of words.
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2 items
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Updated
llama-qLoRA
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9713
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: 1e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9835 | 0.3350 | 500 | 2.0047 |
| 1.97 | 0.6700 | 1000 | 1.9901 |
| 1.9764 | 1.0050 | 1500 | 1.9838 |
| 1.9714 | 1.3400 | 2000 | 1.9799 |
| 1.9547 | 1.6750 | 2500 | 1.9770 |
| 1.981 | 2.0101 | 3000 | 1.9747 |
| 1.9841 | 2.3451 | 3500 | 1.9729 |
| 1.9469 | 2.6801 | 4000 | 1.9713 |
Framework versions
- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for dhanishetty/Llama-3-8B-Adapters
Base model
meta-llama/Meta-Llama-3-8B