--- license: apache-2.0 base_model: facebook/convnextv2-femto-1k-224 tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: 10-convnextv2-femto-1k-224-finetuned-spiderTraining20-500 results: [] --- # 10-convnextv2-femto-1k-224-finetuned-spiderTraining20-500 This model is a fine-tuned version of [facebook/convnextv2-femto-1k-224](https://huggingface.co/facebook/convnextv2-femto-1k-224) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.4856 - Accuracy: 0.8388 - Precision: 0.8342 - Recall: 0.8349 - F1: 0.8332 ## 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: 5e-05 - train_batch_size: 25 - eval_batch_size: 25 - seed: 42 - distributed_type: multi-GPU - gradient_accumulation_steps: 4 - total_train_batch_size: 100 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | 1.9569 | 1.0 | 80 | 1.7758 | 0.5065 | 0.5330 | 0.5075 | 0.4959 | | 1.05 | 2.0 | 160 | 0.9583 | 0.7207 | 0.7400 | 0.7158 | 0.7102 | | 0.8342 | 3.0 | 240 | 0.7517 | 0.7568 | 0.7747 | 0.7420 | 0.7409 | | 0.7 | 4.0 | 320 | 0.6801 | 0.7928 | 0.7921 | 0.7890 | 0.7826 | | 0.5956 | 5.0 | 400 | 0.5913 | 0.8128 | 0.8130 | 0.8082 | 0.8061 | | 0.572 | 6.0 | 480 | 0.5533 | 0.8278 | 0.8259 | 0.8223 | 0.8217 | | 0.4786 | 7.0 | 560 | 0.5108 | 0.8348 | 0.8319 | 0.8308 | 0.8302 | | 0.4201 | 8.0 | 640 | 0.5064 | 0.8318 | 0.8286 | 0.8248 | 0.8252 | | 0.4486 | 9.0 | 720 | 0.4951 | 0.8408 | 0.8364 | 0.8363 | 0.8350 | | 0.4382 | 10.0 | 800 | 0.4856 | 0.8388 | 0.8342 | 0.8349 | 0.8332 | ### Framework versions - Transformers 4.33.3 - Pytorch 2.0.1+cu117 - Datasets 2.14.5 - Tokenizers 0.13.3