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:
| name | learning_rate | decay | beta_1 | beta_2 | epsilon | amsgrad | training_precision |
|---|---|---|---|---|---|---|---|
| Adam | 0.0010000000474974513 | 0.0 | 0.8999999761581421 | 0.9990000128746033 | 1e-07 | False | float32 |
Training Metrics
| Epochs | Train Loss |
|---|---|
| 1 | 4.71 |
Model Plot
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# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://merve/hyperparam_table")