99ae5664-917e-454a-be8b-566f8048cc7f
This model is a fine-tuned version of NousResearch/Yarn-Llama-2-13b-64k on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.8388
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: 0.000204
- train_batch_size: 4
- eval_batch_size: 4
- seed: 40
- 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: 250
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0001 | 1 | 3.8790 |
| 6.0053 | 0.0027 | 50 | 2.9736 |
| 5.9929 | 0.0054 | 100 | 2.9220 |
| 5.9714 | 0.0082 | 150 | 2.8836 |
| 6.0665 | 0.0109 | 200 | 2.8421 |
| 6.0863 | 0.0136 | 250 | 2.8388 |
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-2-13b-64k