metadata
library_name: transformers
license: apache-2.0
base_model: HuggingFaceTB/SmolLM2-135M
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: bias-scorer-smollm2-135m
results: []
bias-scorer-smollm2-135m
This model is a fine-tuned version of HuggingFaceTB/SmolLM2-135M on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4030
- F1: 0.8236
- Accuracy: 0.8297
- Precision: 0.8205
- Recall: 0.8297
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 0 | 0 | 0.6116 | 0.7504 | 0.7313 | 0.7927 | 0.7313 |
| 0.4266 | 0.5044 | 10000 | 0.4032 | 0.8235 | 0.8297 | 0.8204 | 0.8297 |
| 0.3763 | 1.0088 | 20000 | 0.4030 | 0.8236 | 0.8297 | 0.8205 | 0.8297 |
| 0.3956 | 1.5132 | 30000 | 0.4030 | 0.8236 | 0.8297 | 0.8205 | 0.8297 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3