End of training

README.md

@@ -10,23 +10,7 @@ metrics:
 - f1
 model-index:
 - name: finetuning-sentiment-model-3000-samples
-  results:
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: imdb
-      type: imdb
-      config: plain_text
-      split: test
-      args: plain_text
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.8666666666666667
-    - name: F1
-      type: f1
-      value: 0.8684210526315789
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -36,9 +20,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3161
-- Accuracy: 0.8667
-- F1: 0.8684
+- Loss: 0.6467
+- Accuracy: 0.77
+- F1: 0.7544
 
 ## Model description
 
@@ -72,6 +56,6 @@ The following hyperparameters were used during training:
 ### Framework versions
 
 - Transformers 4.35.2
-- Pytorch 1.13.1+cu117
+- Pytorch 2.1.0+cu118
 - Datasets 2.15.0
 - Tokenizers 0.15.0

runs/Nov19_22-29-11_c37cab3f2367/events.out.tfevents.1700433350.c37cab3f2367.475.1

@@ -0,0 +1,3 @@
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+oid sha256:52c7bed4e5a2b1107df103ebe3dd84cd349a0576bec96043b3f0b637bbcd906c
+size 457