---
library_name: transformers
license: apache-2.0
base_model: HuggingFaceTB/SmolLM2-135M-Instruct
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: toxicity-scorer-smollm2-135m-it-freeze
  results: []
---

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# toxicity-scorer-smollm2-135m-it-freeze

This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3147
- F1: 0.8264
- Accuracy: 0.8745
- Precision: 0.8384
- Recall: 0.8745

## 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: 44
- eval_batch_size: 44
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 352
- total_eval_batch_size: 352
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1     | Accuracy | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
| No log        | 0      | 0    | 0.9227          | 0.6386 | 0.5685   | 0.7480    | 0.5685 |
| 0.3196        | 1.5596 | 5000 | 0.3147          | 0.8264 | 0.8745   | 0.8384    | 0.8745 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3