llama3-1_8b_mlfoundations-dev-stackexchange_quantumcomputing
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on the mlfoundations-dev/stackexchange_quantumcomputing dataset. It achieves the following results on the evaluation set:
- Loss: 0.8230
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 512
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9091 | 0.9846 | 20 | 0.8880 |
| 0.8243 | 1.9692 | 40 | 0.8400 |
| 0.7609 | 2.9538 | 60 | 0.8230 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.1
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Model tree for mlfoundations-dev/llama3-1_8b_mlfoundations-dev-stackexchange_quantumcomputing
Base model
meta-llama/Llama-3.1-8B