vm-llama3-lr4e-5-be5e-4-r8
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on the alphamath dataset. It achieves the following results on the evaluation set:
- Loss: 0.1354
- Accuracy: 0.4164
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: 4e-05
- train_batch_size: 26
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 5
- total_train_batch_size: 1040
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 12
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.2619 | 5.0 | 500 | 0.1481 | 0.3158 |
0.2206 | 10.0 | 1000 | 0.1354 | 0.4080 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for sailplane/vm-llama3-lr4e-5-be5e-4-r8
Base model
meta-llama/Llama-3.1-8B