metadata
library_name: transformers
license: apache-2.0
base_model: HuggingFaceTB/SmolLM2-1.7B
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
model-index:
- name: HuggingFaceTB/SmolLM2-1.7B
results: []
HuggingFaceTB/SmolLM2-1.7B
This model is a fine-tuned version of HuggingFaceTB/SmolLM2-1.7B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7823
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 64
- 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_ratio: 0.05
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3348 | 0.0551 | 200 | 1.2704 |
| 1.0411 | 0.1101 | 400 | 1.0435 |
| 1.0483 | 0.1652 | 600 | 0.9694 |
| 0.8801 | 0.2202 | 800 | 0.9227 |
| 0.8996 | 0.2753 | 1000 | 0.8888 |
| 0.8682 | 0.3303 | 1200 | 0.8648 |
| 0.8757 | 0.3854 | 1400 | 0.8468 |
| 0.8441 | 0.4404 | 1600 | 0.8311 |
| 0.8197 | 0.4955 | 1800 | 0.8206 |
| 0.7807 | 0.5505 | 2000 | 0.8090 |
| 0.7757 | 0.6056 | 2200 | 0.8015 |
| 0.7818 | 0.6607 | 2400 | 0.7957 |
| 0.8235 | 0.7157 | 2600 | 0.7915 |
| 0.7854 | 0.7708 | 2800 | 0.7883 |
| 0.7958 | 0.8258 | 3000 | 0.7863 |
| 0.8192 | 0.8809 | 3200 | 0.7829 |
| 0.765 | 0.9359 | 3400 | 0.7824 |
| 0.7939 | 0.9910 | 3600 | 0.7824 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.21.0