96c11406-cdee-4570-a407-ce912c5624b9
This model is a fine-tuned version of NousResearch/Yarn-Mistral-7b-64k on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7090
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: 0.000201
- train_batch_size: 4
- eval_batch_size: 4
- seed: 10
- 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 | 0.0002 | 1 | 1.0562 |
| 1.5047 | 0.0078 | 50 | 0.9274 |
| 1.3497 | 0.0155 | 100 | 0.9256 |
| 1.3004 | 0.0233 | 150 | 0.9040 |
| 1.2977 | 0.0310 | 200 | 0.8848 |
| 1.202 | 0.0388 | 250 | 0.8283 |
| 1.0932 | 0.0465 | 300 | 0.7898 |
| 1.086 | 0.0543 | 350 | 0.7522 |
| 1.0237 | 0.0620 | 400 | 0.7235 |
| 1.0146 | 0.0698 | 450 | 0.7110 |
| 0.9788 | 0.0775 | 500 | 0.7090 |
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-Mistral-7b-64k