--- tags: - generated_from_keras_callback model-index: - name: Prototypeu/bart-base-finetuned-tldrhq-cnn-dailymail results: [] --- # Prototypeu/bart-base-finetuned-tldrhq-cnn-dailymail This model is a fine-tuned version of [Prototypeu/bart-base-finetuned-xsum](https://huggingface.co/Prototypeu/bart-base-finetuned-xsum) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 1.5049 - Train Logits Loss: 1.5049 - Train Rouge1: 28.1795 - Train Rouge2: 14.0392 - Train Rougel: 23.7617 - Train Rougelsum: 26.5583 - Train Gen Len: 19.0 - Epoch: 4 ## 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: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 3e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 255113, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 32000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.98, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Train Logits Loss | Train Rouge1 | Train Rouge2 | Train Rougel | Train Rougelsum | Train Gen Len | Epoch | |:----------:|:-----------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:-----:| | 2.9074 | 2.9074 | 26.9164 | 12.6984 | 22.4321 | 25.2287 | 19.0 | 0 | | 1.9368 | 1.9368 | 28.0165 | 13.8906 | 23.4187 | 26.3779 | 19.0 | 1 | | 1.7246 | 1.7246 | 27.6022 | 13.5255 | 23.2301 | 25.9923 | 19.0 | 2 | | 1.5945 | 1.5945 | 28.0347 | 13.7045 | 23.4851 | 26.3488 | 19.0 | 3 | | 1.5049 | 1.5049 | 28.1795 | 14.0392 | 23.7617 | 26.5583 | 19.0 | 4 | ### Framework versions - Transformers 4.17.0 - TensorFlow 2.6.0 - Datasets 2.0.0 - Tokenizers 0.11.6