distilled_chat_math
This model is a fine-tuned version of HuggingFaceTB/SmolLM-135M-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1308
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.1408 | 1.3378 | 500 | 0.1368 |
| 0.1268 | 2.6756 | 1000 | 0.1308 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3
- Downloads last month
- 152
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for niteshagarwala/distilled_chat_math
Base model
HuggingFaceTB/SmolLM-135M
Quantized
HuggingFaceTB/SmolLM-135M-Instruct