End of training

README.md

@@ -1,20 +1,22 @@
 ---
 library_name: transformers
 license: mit
-base_model: MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli
+base_model: roberta-base
 tags:
 - generated_from_trainer
 model-index:
-- name: inductive-classifier
+- name: inductiv-binary-classifier
   results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# inductive-classifier
+# inductiv-binary-classifier
 
-This model is a fine-tuned version of [MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli](https://huggingface.co/MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli) on an unknown dataset.
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0000
 
 ## Model description
 
@@ -34,15 +36,20 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 4
+- train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 2
+- mixed_precision_training: Native AMP
 
 ### Training results
 
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.0           | 1.0   | 2250 | 0.0000          |
+| 0.0           | 2.0   | 4500 | 0.0000          |
 
 
 ### Framework versions