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library_name: peft
license: apache-2.0
base_model: HuggingFaceTB/SmolLM2-360M
tags:
- base_model:adapter:HuggingFaceTB/SmolLM2-360M
- lora
- transformers
metrics:
- accuracy
- precision
- recall
model-index:
- name: HuggingFaceTB_SmolLM2-360M_StereoDetect_Model
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# HuggingFaceTB_SmolLM2-360M_StereoDetect_Model
This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-360M](https://huggingface.co/HuggingFaceTB/SmolLM2-360M) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3245
- Accuracy: 0.8906
- Balanced Accuracy: 0.8935
- F1 Weighted: 0.8905
- F1 Macro: 0.8914
- Precision: 0.8919
- Recall: 0.8906
## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Balanced Accuracy | F1 Weighted | F1 Macro | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:-----------:|:--------:|:---------:|:------:|
| 0.7655 | 1.0 | 760 | 0.3760 | 0.8399 | 0.8424 | 0.8371 | 0.8382 | 0.8484 | 0.8399 |
| 0.2651 | 2.0 | 1520 | 0.2842 | 0.8825 | 0.8840 | 0.8815 | 0.8825 | 0.8890 | 0.8825 |
| 0.1856 | 3.0 | 2280 | 0.2940 | 0.8802 | 0.8835 | 0.8795 | 0.8806 | 0.8824 | 0.8802 |
| 0.1307 | 4.0 | 3040 | 0.3245 | 0.8906 | 0.8935 | 0.8905 | 0.8914 | 0.8919 | 0.8906 |
| 0.0938 | 5.0 | 3800 | 0.3328 | 0.8871 | 0.8898 | 0.8871 | 0.8877 | 0.8875 | 0.8871 |
### Framework versions
- PEFT 0.19.1
- Transformers 4.51.3
- Pytorch 2.5.1+cu121
- Datasets 4.8.5
- Tokenizers 0.21.4 |