End of training

README.md

@@ -1,23 +1,24 @@
 ---
-base_model: google/reformer-crime-and-punishment
+license: cc-by-4.0
+base_model: l3cube-pune/telugu-bert
 tags:
 - generated_from_trainer
 metrics:
 - accuracy
 model-index:
-- name: reformer_model
+- name: telugu-bert
   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. -->
 
-# reformer_model
+# telugu-bert
 
-This model is a fine-tuned version of [google/reformer-crime-and-punishment](https://huggingface.co/google/reformer-crime-and-punishment) on the None dataset.
+This model is a fine-tuned version of [l3cube-pune/telugu-bert](https://huggingface.co/l3cube-pune/telugu-bert) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6693
-- Accuracy: 0.561
+- Loss: 0.3905
+- Accuracy: 0.848
 
 ## Model description
 
@@ -48,13 +49,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.6841        | 1.0   | 625  | 0.6725          | 0.559    |
-| 0.6789        | 2.0   | 1250 | 0.6693          | 0.561    |
+| 0.5958        | 1.0   | 625  | 0.4664          | 0.807    |
+| 0.4502        | 2.0   | 1250 | 0.3905          | 0.848    |
 
 
 ### Framework versions
 
-- Transformers 4.40.2
+- Transformers 4.41.2
 - Pytorch 2.3.0+cpu
-- Datasets 2.19.1
+- Datasets 2.20.0
 - Tokenizers 0.19.1