metadata

library_name: transformers
license: apache-2.0
base_model: HuggingFaceTB/SmolLM2-360M
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
  - precision
  - recall
model-index:
  - name: toxicity-scorer-smollm2-360m-freeze
    results: []

toxicity-scorer-smollm2-360m-freeze

This model is a fine-tuned version of HuggingFaceTB/SmolLM2-360M on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.7434
F1: 0.6049
Accuracy: 0.5261
Precision: 0.7390
Recall: 0.5261

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: 1e-06
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	0.7481	0.6025	0.5231	0.7383	0.5231
0.7489	1.5277	5000	0.7434	0.6049	0.5261	0.7390	0.5261

Framework versions

Transformers 4.46.3
Pytorch 2.5.1
Datasets 3.1.0
Tokenizers 0.20.3