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-pt-pl50
-  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: 19.8017
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -17,14 +32,14 @@ should probably proofread and complete it, then remove this comment. -->
 
 # liputan6-pt-pl50
 
-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: 3.7381
-- Rouge1: 19.5385
-- Rouge2: 5.1106
-- Rougel: 16.7601
-- Rougelsum: 17.9271
-- Gen Len: 29.142
+- Loss: 3.7533
+- Rouge1: 19.8017
+- Rouge2: 5.8239
+- Rougel: 17.0737
+- Rougelsum: 18.0279
+- Gen Len: 30.789
 
 ## Model description
 

all_results.json

@@ -0,0 +1,29 @@
+{
+    "epoch": 5.0,
+    "eval_gen_len": 30.789,
+    "eval_loss": 3.7532596588134766,
+    "eval_rouge1": 19.8017,
+    "eval_rouge2": 5.8239,
+    "eval_rougeL": 17.0737,
+    "eval_rougeLsum": 18.0279,
+    "eval_runtime": 1387.1111,
+    "eval_samples": 1000,
+    "eval_samples_per_second": 0.721,
+    "eval_steps_per_second": 0.023,
+    "predict_gen_len": 30.491,
+    "predict_loss": 3.4927051067352295,
+    "predict_rouge1": 23.6497,
+    "predict_rouge2": 7.8208,
+    "predict_rougeL": 19.7078,
+    "predict_rougeLsum": 21.5526,
+    "predict_runtime": 1458.4576,
+    "predict_samples": 1000,
+    "predict_samples_per_second": 0.686,
+    "predict_steps_per_second": 0.022,
+    "total_flos": 3877644533760000.0,
+    "train_loss": 3.802120681036086,
+    "train_runtime": 4251.699,
+    "train_samples": 1000,
+    "train_samples_per_second": 1.176,
+    "train_steps_per_second": 0.074
+}

eval_results.json

@@ -0,0 +1,13 @@
+{
+    "epoch": 5.0,
+    "eval_gen_len": 30.789,
+    "eval_loss": 3.7532596588134766,
+    "eval_rouge1": 19.8017,
+    "eval_rouge2": 5.8239,
+    "eval_rougeL": 17.0737,
+    "eval_rougeLsum": 18.0279,
+    "eval_runtime": 1387.1111,
+    "eval_samples": 1000,
+    "eval_samples_per_second": 0.721,
+    "eval_steps_per_second": 0.023
+}

predict_results.json

@@ -0,0 +1,12 @@
+{
+    "predict_gen_len": 30.491,
+    "predict_loss": 3.4927051067352295,
+    "predict_rouge1": 23.6497,
+    "predict_rouge2": 7.8208,
+    "predict_rougeL": 19.7078,
+    "predict_rougeLsum": 21.5526,
+    "predict_runtime": 1458.4576,
+    "predict_samples": 1000,
+    "predict_samples_per_second": 0.686,
+    "predict_steps_per_second": 0.022
+}

train_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 5.0,
+    "total_flos": 3877644533760000.0,
+    "train_loss": 3.802120681036086,
+    "train_runtime": 4251.699,
+    "train_samples": 1000,
+    "train_samples_per_second": 1.176,
+    "train_steps_per_second": 0.074
+}

trainer_state.json

@@ -0,0 +1,130 @@
+{
+  "best_metric": 19.7665,
+  "best_model_checkpoint": "bin/liputan6-pt-pl50/checkpoint-252",
+  "epoch": 5.0,
+  "eval_steps": 500,
+  "global_step": 315,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
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+      "grad_norm": 1.0756858587265015,
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+      "eval_loss": 3.9912047386169434,
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+      "eval_rouge2": 3.6927,
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+      "eval_rougeLsum": 15.3151,
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+      "eval_rouge2": 4.2061,
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+  "logging_steps": 500,
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+  "num_input_tokens_seen": 0,
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+}