Update README.md

README.md

@@ -11,7 +11,10 @@ probably proofread and complete it, then remove this comment. -->
 
 # xtremedistil-l6-h256-uncased-nli
 
-The model base is xtremedistil-l6-h256-uncased. It has been fine-tuned on: snli, wanli, mnli, anli, scitail
+The model base is [xtremedistil-l6-h256-uncased](https://huggingface.co/microsoft/xtremedistil-l6-h256-uncased). 
+It has been fine-tuned on: [snli](https://huggingface.co/datasets/snli), [wanli](https://huggingface.co/datasets/alisawuffles/WANLI), 
+[mnli](https://huggingface.co/datasets/multi_nli), [anli](https://huggingface.co/datasets/anli), 
+[scitail](https://huggingface.co/datasets/scitail)
 
 ## Model description
 
@@ -29,10 +32,6 @@ More information needed
 
 ### Training hyperparameters
 
-The following hyperparameters were used during training:
-- 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': 2214, 'end_learning_rate': 1e-05, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
-- training_precision: float32
-
 ### Training results
 
 It achieved the following accuracy during training (on validation sets):