metadata
library_name: transformers
base_model: llama_small_config.json
tags:
- generated_from_trainer
model-index:
- name: llama-3.2-350M-fourier_multiplication_dataset
results: []
llama-3.2-350M-fourier_multiplication_dataset
This model is a fine-tuned version of llama_small_config.json on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7836
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: 0.0005
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.6476 | 0.1415 | 1000 | 2.5967 |
| 2.0109 | 0.2831 | 2000 | 2.0067 |
| 2.1092 | 0.4246 | 3000 | 2.1034 |
| 1.9086 | 0.5661 | 4000 | 1.9051 |
| 1.8537 | 0.7076 | 5000 | 1.8473 |
| 1.7953 | 0.8492 | 6000 | 1.7943 |
| 1.7858 | 0.9907 | 7000 | 1.7836 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.3.1+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0