oh-dcft-v3.1-llama-3.1-405b-qwen
This model is a fine-tuned version of Qwen/Qwen2.5-7B on the mlfoundations-dev/oh-dcft-v3.1-llama-3.1-405b dataset. It achieves the following results on the evaluation set:
- Loss: 0.2944
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: 5e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- total_train_batch_size: 128
- total_eval_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3104 | 1.0 | 1752 | 0.2994 |
| 0.241 | 2.0 | 3504 | 0.2880 |
| 0.1946 | 3.0 | 5256 | 0.2944 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.4.0
- Datasets 3.0.2
- Tokenizers 0.20.3
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