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---
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: []
---
<!-- 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-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
|