ratish/DBERT_CleanDesc_Collision_v2.1.4

1---2license: apache-2.03tags:4- generated_from_keras_callback5model-index:6- name: ratish/DBERT_CleanDesc_Collision_v2.1.47  results: []8---9 10<!-- This model card has been generated automatically according to the information Keras had access to. You should11probably proofread and complete it, then remove this comment. -->12 13# ratish/DBERT_CleanDesc_Collision_v2.1.414 15This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.16It achieves the following results on the evaluation set:17- Train Loss: 0.343818- Validation Loss: 1.446719- Train Accuracy: 0.589720- Epoch: 1121 22## Model description23 24More information needed25 26## Intended uses & limitations27 28More information needed29 30## Training and evaluation data31 32More information needed33 34## Training procedure35 36### Training hyperparameters37 38The following hyperparameters were used during training:39- optimizer: {'name': 'Adam', '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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 4575, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}40- training_precision: float3241 42### Training results43 44| Train Loss | Validation Loss | Train Accuracy | Epoch |45|:----------:|:---------------:|:--------------:|:-----:|46| 1.6148     | 1.7151          | 0.3077         | 0     |47| 1.4783     | 1.7263          | 0.3077         | 1     |48| 1.3926     | 1.6779          | 0.4103         | 2     |49| 1.2462     | 1.5778          | 0.4359         | 3     |50| 1.0592     | 1.5154          | 0.4359         | 4     |51| 0.8814     | 1.5370          | 0.4615         | 5     |52| 0.7554     | 1.4250          | 0.5385         | 6     |53| 0.6303     | 1.4385          | 0.5641         | 7     |54| 0.5458     | 1.3870          | 0.4872         | 8     |55| 0.4808     | 1.3459          | 0.5385         | 9     |56| 0.4098     | 1.5049          | 0.5385         | 10    |57| 0.3438     | 1.4467          | 0.5897         | 11    |58 59 60### Framework versions61 62- Transformers 4.28.163- TensorFlow 2.12.064- Datasets 2.12.065- Tokenizers 0.13.366