End of training

README.md

@@ -1,24 +1,24 @@
 ---
-license: apache-2.0
-base_model: distilbert/distilbert-base-uncased
+license: mit
+base_model: ai4bharat/indic-bert
 tags:
 - generated_from_trainer
 metrics:
 - accuracy
 model-index:
-- name: DistilBERTForClassification
+- name: test_model
   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. -->
 
-# DistilBERTForClassification
+# test_model
 
-This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
+This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3499
-- Accuracy: 0.857
+- Loss: 0.5251
+- Accuracy: 0.7788
 
 ## Model description
 
@@ -49,13 +49,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.5119        | 1.0   | 625  | 0.3677          | 0.832    |
-| 0.3729        | 2.0   | 1250 | 0.3499          | 0.857    |
+| No log        | 1.0   | 65   | 0.5317          | 0.7788   |
+| No log        | 2.0   | 130  | 0.5251          | 0.7788   |
 
 
 ### Framework versions
 
-- Transformers 4.32.1
-- Pytorch 2.2.1+cpu
-- Datasets 2.12.0
-- Tokenizers 0.13.2
+- Transformers 4.41.2
+- Pytorch 2.3.0+cpu
+- Datasets 2.17.0
+- Tokenizers 0.19.1