Distilbert 8 4 1.25 85 65 75

--- library_name: transformers license: apache-2.0 base_model: distilbert/distilbert-base-uncased tags: - generated_from_trainer model-index: - name: distilbert-8-4-1.25-85-65-75 results: [] --- # distilbert-8-4-1.25-85-65-75 This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3073 - F1 Micro: 0.7857 - F1 Macro: 0.7410 - Precision Micro: 0.8238 - Recall Micro: 0.7510 ## 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: 2e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 6 - total_train_batch_size: 24 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 3143 - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Precision Micro | Recall Micro | |:-------------:|:-----:|:-----:|:---------------:|:---------:|:---------:|:----------------:|:-------------:| | 1.8702 | 1.0 | 10479 | 0.3111 | 0.7648 | 0.7128 | 0.8162 | 0.7195 | | 1.8551 | 2.0 | 20958 | 0.3090 | 0.7862 | 0.7477 | 0.8178 | 0.7569 | | 1.8460 | 3.0 | 31437 | 0.3082 | 0.7886 | 0.7512 | 0.8266 | 0.7539 | ### Framework versions - Transformers 5.10.2 - Pytorch 2.11.0+cu128 - Datasets 4.8.5 - Tokenizers 0.22.2