axolotl version: 0.6.0
base_model: mrcuddle/Dark-Hermes3-Llama3.2-3B
dataloader_num_workers: 4
datasets:
- dataset_prepared_path: last_run_prepared
path: llamafactory/alpaca_en
type: alpaca
eval_steps: 500
evaluation_strategy: steps
fp16: true
gradient_accumulation_steps: 8
gradient_checkpointing: false
learning_rate: 2e-5
load_in_4bit: false
logging_dir: /content/outputs/logs
logging_steps: 10
lr_scheduler: cosine
lr_scheduler_type: cosine
micro_batch_size: 1
num_train_epochs: 3
optimizer: paged_adamw_8bit
output_dir: /content/outputs
overwrite_output_dir: true
per_device_train_batch_size: 4
save_steps: 500
save_total_limit: 2
use_peft: false
val_set_size: 0.05
warmup_steps: 100
content/outputs
This model is a fine-tuned version of mrcuddle/Dark-Hermes3-Llama3.2-3B on the llamafactory/alpaca_en dataset. It achieves the following results on the evaluation set:
- Loss: 1.1205
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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use paged_adamw_8bit 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: 100
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0002 | 1 | 2.4030 |
| 1.2572 | 0.0814 | 500 | 1.1935 |
| 1.3061 | 0.1629 | 1000 | 1.1865 |
| 1.2733 | 0.2443 | 1500 | 1.1864 |
| 1.265 | 0.3258 | 2000 | 1.1753 |
| 1.2436 | 0.4072 | 2500 | 1.1542 |
| 1.2935 | 0.4887 | 3000 | 1.1448 |
| 1.2595 | 0.5701 | 3500 | 1.1348 |
| 1.2896 | 0.6515 | 4000 | 1.1295 |
| 1.2081 | 0.7330 | 4500 | 1.1236 |
| 1.2451 | 0.8144 | 5000 | 1.1212 |
| 1.2134 | 0.8959 | 5500 | 1.1205 |
| 1.2437 | 0.9773 | 6000 | 1.1205 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0