--- license: apache-2.0 base_model: google/flan-t5-small tags: - generated_from_keras_callback model-index: - name: t5-small-trivia-gpu-ca2q results: [] --- # t5-small-trivia-gpu-ca2q This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co./google/flan-t5-small) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 1.1645 - Validation Loss: 1.4135 - Epoch: 2
{'eval_loss': 1.4102883338928223, 'eval_bleu': 17.300335685770165, 'eval_rouge1': 53.45, 'eval_rouge2': 30.12, 'eval_rougeL': 46.5, 'eval_rougeLsum': 46.5, 'eval_exact': 0.018948595860460597, 'eval_runtime': 230.3707, 'eval_samples_per_second': 44.671, 'eval_steps_per_second': 1.398}## 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': 'Adafactor', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 0.001, 'beta_2_decay': -0.8, 'epsilon_1': 1e-30, 'epsilon_2': 0.001, 'clip_threshold': 1.0, 'relative_step': False} - training_precision: float32 ### Training results | Train Loss | Validation Loss | Epoch | |:----------:|:---------------:|:-----:| | 1.6697 | 1.4399 | 0 | | 1.3467 | 1.4110 | 1 | | 1.1645 | 1.4135 | 2 | ### Framework versions - Transformers 4.31.0 - TensorFlow 2.13.0 - Datasets 2.14.3 - Tokenizers 0.13.3