End of training

README.md

@@ -1,4 +1,6 @@
 ---
+language:
+- id
 license: apache-2.0
 base_model: LazarusNLP/IndoNanoT5-base
 tags:
@@ -9,7 +11,20 @@ metrics:
 - rouge
 model-index:
 - name: liputan6-unipelt
-  results: []
+  results:
+  - task:
+      name: Summarization
+      type: summarization
+    dataset:
+      name: id_liputan6 canonical
+      type: id_liputan6
+      config: canonical
+      split: validation
+      args: canonical
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 1.8031
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -17,13 +32,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # liputan6-unipelt
 
-This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on the id_liputan6 dataset.
+This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on the id_liputan6 canonical dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.3672
-- Rouge1: 5.0669
-- Rouge2: 1.0704
-- Rougel: 3.6335
-- Rougelsum: 4.1011
+- Loss: 2.5645
+- Rouge1: 1.8031
+- Rouge2: 0.4028
+- Rougel: 1.5585
+- Rougelsum: 1.6132
 - Gen Len: 127.0
 
 ## Model description

all_results.json

@@ -1,29 +1,29 @@
 {
     "epoch": 5.0,
     "eval_gen_len": 127.0,
-    "eval_loss": 3.9181036949157715,
-    "eval_rouge1": 6.2596,
-    "eval_rouge2": 1.3631,
-    "eval_rougeL": 5.5527,
-    "eval_rougeLsum": 5.702,
-    "eval_runtime": 3038.3287,
+    "eval_loss": 2.564530849456787,
+    "eval_rouge1": 1.8031,
+    "eval_rouge2": 0.4028,
+    "eval_rougeL": 1.5585,
+    "eval_rougeLsum": 1.6132,
+    "eval_runtime": 2903.5388,
     "eval_samples": 1000,
-    "eval_samples_per_second": 0.329,
+    "eval_samples_per_second": 0.344,
     "eval_steps_per_second": 0.011,
     "predict_gen_len": 127.0,
-    "predict_loss": 3.675906181335449,
-    "predict_rouge1": 8.1435,
-    "predict_rouge2": 1.7586,
-    "predict_rougeL": 6.9904,
-    "predict_rougeLsum": 7.4145,
-    "predict_runtime": 3068.2499,
+    "predict_loss": 2.4079694747924805,
+    "predict_rouge1": 2.3863,
+    "predict_rouge2": 0.6285,
+    "predict_rougeL": 2.0562,
+    "predict_rougeLsum": 2.1567,
+    "predict_runtime": 2906.5636,
     "predict_samples": 1000,
-    "predict_samples_per_second": 0.326,
-    "predict_steps_per_second": 0.01,
+    "predict_samples_per_second": 0.344,
+    "predict_steps_per_second": 0.011,
     "total_flos": 3920273141760000.0,
-    "train_loss": 3.429138425796751,
-    "train_runtime": 4104.3672,
+    "train_loss": 2.8293707469153024,
+    "train_runtime": 4145.4302,
     "train_samples": 1000,
-    "train_samples_per_second": 1.218,
-    "train_steps_per_second": 0.077
+    "train_samples_per_second": 1.206,
+    "train_steps_per_second": 0.076
 }

eval_results.json

@@ -1,13 +1,13 @@
 {
     "epoch": 5.0,
     "eval_gen_len": 127.0,
-    "eval_loss": 3.9181036949157715,
-    "eval_rouge1": 6.2596,
-    "eval_rouge2": 1.3631,
-    "eval_rougeL": 5.5527,
-    "eval_rougeLsum": 5.702,
-    "eval_runtime": 3038.3287,
+    "eval_loss": 2.564530849456787,
+    "eval_rouge1": 1.8031,
+    "eval_rouge2": 0.4028,
+    "eval_rougeL": 1.5585,
+    "eval_rougeLsum": 1.6132,
+    "eval_runtime": 2903.5388,
     "eval_samples": 1000,
-    "eval_samples_per_second": 0.329,
+    "eval_samples_per_second": 0.344,
     "eval_steps_per_second": 0.011
 }

predict_results.json

@@ -1,12 +1,12 @@
 {
     "predict_gen_len": 127.0,
-    "predict_loss": 3.675906181335449,
-    "predict_rouge1": 8.1435,
-    "predict_rouge2": 1.7586,
-    "predict_rougeL": 6.9904,
-    "predict_rougeLsum": 7.4145,
-    "predict_runtime": 3068.2499,
+    "predict_loss": 2.4079694747924805,
+    "predict_rouge1": 2.3863,
+    "predict_rouge2": 0.6285,
+    "predict_rougeL": 2.0562,
+    "predict_rougeLsum": 2.1567,
+    "predict_runtime": 2906.5636,
     "predict_samples": 1000,
-    "predict_samples_per_second": 0.326,
-    "predict_steps_per_second": 0.01
+    "predict_samples_per_second": 0.344,
+    "predict_steps_per_second": 0.011
 }

train_results.json

@@ -1,9 +1,9 @@
 {
     "epoch": 5.0,
     "total_flos": 3920273141760000.0,
-    "train_loss": 3.429138425796751,
-    "train_runtime": 4104.3672,
+    "train_loss": 2.8293707469153024,
+    "train_runtime": 4145.4302,
     "train_samples": 1000,
-    "train_samples_per_second": 1.218,
-    "train_steps_per_second": 0.077
+    "train_samples_per_second": 1.206,
+    "train_steps_per_second": 0.076
 }

trainer_state.json

@@ -1,6 +1,6 @@
 {
-  "best_metric": 6.5087,
-  "best_model_checkpoint": "bin/liputan6-unipelt/checkpoint-63",
+  "best_metric": 5.2587,
+  "best_model_checkpoint": "bin/liputan6-unipelt/checkpoint-189",
   "epoch": 5.0,
   "eval_steps": 500,
   "global_step": 315,
@@ -10,101 +10,101 @@
   "log_history": [
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@@ -112,10 +112,10 @@
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   "logging_steps": 500,