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

# toxicity-scorer-smollm2-135m-freeze

This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M](https://huggingface.co/HuggingFaceTB/SmolLM2-135M) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3011
- F1: 0.8565
- Accuracy: 0.8807
- Precision: 0.8558
- Recall: 0.8807

## 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: 36
- eval_batch_size: 36
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 288
- total_eval_batch_size: 288
- 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     | 1.2430          | 0.5996 | 0.5195   | 0.7569    | 0.5195 |
| 0.3157        | 1.2762 | 5000  | 0.3011          | 0.8562 | 0.8806   | 0.8556    | 0.8806 |
| 0.309         | 2.5523 | 10000 | 0.3011          | 0.8565 | 0.8807   | 0.8558    | 0.8807 |


### Framework versions

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