1.7 KiB
1.7 KiB
library_name, license, base_model, tags, model-index
| library_name | license | base_model | tags | model-index | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| transformers | other | meta-llama/Llama-3.1-8B |
|
|
ds3full_pretrain
This model is a fine-tuned version of meta-llama/Llama-3.1-8B on the cpt_jazz_v3, the cpt_jazz_v3_copy, the cpt_opensource_v3 and the cpt_local_v3 datasets. It achieves the following results on the evaluation set:
- Loss: 1.1027
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-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.1993 | 0.3176 | 200 | 1.1916 |
| 1.1243 | 0.6351 | 400 | 1.1279 |
| 1.1059 | 0.9527 | 600 | 1.1028 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.1+cu128
- Datasets 4.0.0
- Tokenizers 0.22.1