Adapted model to be more general. Accuracy ~60 on Banking77 and ~80 on Atis.

README.md

@@ -4,8 +4,18 @@ tags:
 datasets:
 - clinc/clinc_oos
 widget:
-- text: "Topic %% Customer: How do I get my money back?.\nEND MESSAGE\nChoose one topic that matches customer's issue.\n# renew subscription # account deletion # cancel subscription # resume subscription # refund requests # other # general # item damaged # malfunction # hello # intro # question\nClass name: "
-  example_title: "Open Label Intent Classification"
+- text: 'Topic %% Customer: How do I get my money back?.
+
+    END MESSAGE
+
+    Choose one topic that matches customer''s issue.
+
+    # renew subscription # account deletion # cancel subscription # resume subscription
+    # refund requests # other # general # item damaged # malfunction # hello # intro
+    # question
+
+    Class name: '
+  example_title: Open Label Intent Classification
 ---
 
 # Prompt Structure

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "archived_experiments/f1w_0.87_m:flan-t5-base_e:2_b:8_t:06232024-23:03:05_ncs:True_ups:False_udl:False_nnp:True_best/models/flan-t5-base",
+  "_name_or_path": "archived_experiments/b0.00_f1w_0.86_m:flan-t5-base_e:3_b:8_t:07122024-14:28:46_ncs:True_ups:False_udl:False_nnp:True_eet:False/models/flan-t5-base",
   "architectures": [
     "T5ForConditionalGeneration"
   ],

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6178a193ae93e675d20911f8cfb4b19735208b1d846a4ef59d64ed6f1d42e620
+oid sha256:e809966c98ce7c7e00bcc246174b5e9404912685bae6f0491b2b6c72282baa2c
 size 990345064