941ddf97-bf7c-48ec-ac45-f1d6caf81cb9
This model is a fine-tuned version of NousResearch/Yarn-Llama-2-7b-64k on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4409
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: 0.000217
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0001 | 1 | 1.9391 |
| 3.2189 | 0.0042 | 50 | 1.6137 |
| 3.3715 | 0.0083 | 100 | 1.6578 |
| 3.2716 | 0.0125 | 150 | 1.6378 |
| 3.3242 | 0.0167 | 200 | 1.6002 |
| 3.1776 | 0.0208 | 250 | 1.5903 |
| 3.1833 | 0.0250 | 300 | 1.5184 |
| 3.3401 | 0.0292 | 350 | 1.4727 |
| 3.0568 | 0.0334 | 400 | 1.4501 |
| 3.2673 | 0.0375 | 450 | 1.4426 |
| 3.2601 | 0.0417 | 500 | 1.4409 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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Base model
NousResearch/Yarn-Llama-2-7b-64k