End of training

README.md

@@ -16,15 +16,15 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [maximuspowers/bert-philosophy-adapted](https://huggingface.co/maximuspowers/bert-philosophy-adapted) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7061
-- Exact Match Accuracy: 0.375
-- Macro Precision: 0.4943
-- Macro Recall: 0.3242
-- Macro F1: 0.3655
-- Micro Precision: 0.7778
-- Micro Recall: 0.4912
-- Micro F1: 0.6022
-- Hamming Loss: 0.0544
+- Loss: 0.5015
+- Exact Match Accuracy: 0.45
+- Macro Precision: 0.3892
+- Macro Recall: 0.3912
+- Macro F1: 0.3626
+- Micro Precision: 0.775
+- Micro Recall: 0.5439
+- Micro F1: 0.6392
+- Hamming Loss: 0.0515
 
 ## Model description
 

all_results.json

@@ -1,5 +1,17 @@
 {
     "epoch": 110.0,
+    "eval_exact_match_accuracy": 0.45,
+    "eval_hamming_loss": 0.051470588235294115,
+    "eval_loss": 0.5014987587928772,
+    "eval_macro_f1": 0.3625902992776057,
+    "eval_macro_precision": 0.3892156862745098,
+    "eval_macro_recall": 0.3911764705882353,
+    "eval_micro_f1": 0.6391752577319587,
+    "eval_micro_precision": 0.775,
+    "eval_micro_recall": 0.543859649122807,
+    "eval_runtime": 0.2083,
+    "eval_samples_per_second": 192.015,
+    "eval_steps_per_second": 24.002,
     "total_flos": 0.0,
     "train_loss": 0.48885808966376565,
     "train_runtime": 558.1593,

runs/Jun15_18-16-43_309caa596f42/events.out.tfevents.1750012000.309caa596f42.1965.1

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:60651201ad14bf0ffb9c6a14c3f303796d084f28da067c8af522cbe60e2438c1
+size 5853

test_results.json

@@ -1,15 +1,15 @@
 {
-    "epoch": 50.0,
-    "eval_exact_match_accuracy": 0.425,
-    "eval_hamming_loss": 0.05,
-    "eval_loss": 0.44675666093826294,
-    "eval_macro_f1": 0.22477092910529442,
-    "eval_macro_precision": 0.307843137254902,
-    "eval_macro_recall": 0.22205882352941175,
-    "eval_micro_f1": 0.6046511627906976,
-    "eval_micro_precision": 0.896551724137931,
-    "eval_micro_recall": 0.45614035087719296,
-    "eval_runtime": 0.2085,
-    "eval_samples_per_second": 191.847,
-    "eval_steps_per_second": 23.981
+    "epoch": 110.0,
+    "eval_exact_match_accuracy": 0.45,
+    "eval_hamming_loss": 0.051470588235294115,
+    "eval_loss": 0.5014987587928772,
+    "eval_macro_f1": 0.3625902992776057,
+    "eval_macro_precision": 0.3892156862745098,
+    "eval_macro_recall": 0.3911764705882353,
+    "eval_micro_f1": 0.6391752577319587,
+    "eval_micro_precision": 0.775,
+    "eval_micro_recall": 0.543859649122807,
+    "eval_runtime": 0.2083,
+    "eval_samples_per_second": 192.015,
+    "eval_steps_per_second": 24.002
 }