hansken_human_hql_v2
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the hansh/hansken_hql_large dataset. It achieves the following results on the evaluation set:
- Loss: 0.3031
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 |
|---|---|---|---|
| 0.3676 | 0.9994 | 788 | 0.3796 |
| 0.2968 | 2.0 | 1577 | 0.3381 |
| 0.2658 | 2.9994 | 2365 | 0.3186 |
| 0.2389 | 4.0 | 3154 | 0.3031 |
| 0.2098 | 4.9994 | 3942 | 0.3035 |
| 0.185 | 6.0 | 4731 | 0.3079 |
| 0.1707 | 6.9994 | 5519 | 0.3125 |
| 0.1578 | 8.0 | 6308 | 0.3237 |
| 0.1426 | 8.9994 | 7096 | 0.3326 |
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_v2
Base model
meta-llama/Llama-3.1-8B Finetuned
meta-llama/Llama-3.1-8B-Instruct