hansken_human_hql_v3
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the hansh/hansken_hql_cot dataset. It achieves the following results on the evaluation set:
- Loss: 0.5017
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: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6267 | 1.0 | 469 | 0.6078 |
| 0.5094 | 2.0 | 938 | 0.5335 |
| 0.513 | 3.0 | 1407 | 0.5142 |
| 0.4306 | 4.0 | 1876 | 0.5044 |
| 0.4128 | 5.0 | 2345 | 0.5017 |
| 0.3924 | 6.0 | 2814 | 0.5093 |
| 0.3684 | 7.0 | 3283 | 0.5168 |
| 0.3403 | 8.0 | 3752 | 0.5338 |
| 0.311 | 9.0 | 4221 | 0.5566 |
| 0.2853 | 10.0 | 4690 | 0.5920 |
Framework versions
- PEFT 0.12.0
- Transformers 4.43.1
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for hansh/hansken_human_hql_v3
Base model
meta-llama/Llama-3.1-8B Finetuned
meta-llama/Llama-3.1-8B-Instruct