End of training

README.md

@@ -1,4 +1,6 @@
 ---
+language:
+- id
 license: apache-2.0
 base_model: LazarusNLP/IndoNanoT5-base
 tags:
@@ -18,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.7690
-- Rouge1: 71.4437
-- Rouge2: 64.1873
-- Rougel: 68.2379
-- Rougelsum: 70.5264
-- Gen Len: 98.6667
+- Rouge1: 71.9504
+- Rouge2: 64.7658
+- Rougel: 68.7524
+- Rougelsum: 70.9978
+- Gen Len: 99.2
 
 ## Model description
 

all_results.json

@@ -0,0 +1,29 @@
+{
+    "epoch": 5.0,
+    "eval_gen_len": 99.2,
+    "eval_loss": 0.7689540982246399,
+    "eval_rouge1": 71.9504,
+    "eval_rouge2": 64.7658,
+    "eval_rougeL": 68.7524,
+    "eval_rougeLsum": 70.9978,
+    "eval_runtime": 872.0619,
+    "eval_samples": 750,
+    "eval_samples_per_second": 0.86,
+    "eval_steps_per_second": 0.028,
+    "predict_gen_len": 98.66391257995735,
+    "predict_loss": 0.737908661365509,
+    "predict_rouge1": 72.4293,
+    "predict_rouge2": 65.4552,
+    "predict_rougeL": 69.5699,
+    "predict_rougeLsum": 71.605,
+    "predict_runtime": 4351.2281,
+    "predict_samples": 3752,
+    "predict_samples_per_second": 0.862,
+    "predict_steps_per_second": 0.027,
+    "total_flos": 4.886428467068928e+16,
+    "train_loss": 0.5789496143837146,
+    "train_runtime": 5011.6095,
+    "train_samples": 14272,
+    "train_samples_per_second": 14.239,
+    "train_steps_per_second": 0.89
+}

eval_results.json

@@ -0,0 +1,13 @@
+{
+    "epoch": 5.0,
+    "eval_gen_len": 99.2,
+    "eval_loss": 0.7689540982246399,
+    "eval_rouge1": 71.9504,
+    "eval_rouge2": 64.7658,
+    "eval_rougeL": 68.7524,
+    "eval_rougeLsum": 70.9978,
+    "eval_runtime": 872.0619,
+    "eval_samples": 750,
+    "eval_samples_per_second": 0.86,
+    "eval_steps_per_second": 0.028
+}

predict_results.json

@@ -0,0 +1,12 @@
+{
+    "predict_gen_len": 98.66391257995735,
+    "predict_loss": 0.737908661365509,
+    "predict_rouge1": 72.4293,
+    "predict_rouge2": 65.4552,
+    "predict_rougeL": 69.5699,
+    "predict_rougeLsum": 71.605,
+    "predict_runtime": 4351.2281,
+    "predict_samples": 3752,
+    "predict_samples_per_second": 0.862,
+    "predict_steps_per_second": 0.027
+}

train_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 5.0,
+    "total_flos": 4.886428467068928e+16,
+    "train_loss": 0.5789496143837146,
+    "train_runtime": 5011.6095,
+    "train_samples": 14272,
+    "train_samples_per_second": 14.239,
+    "train_steps_per_second": 0.89
+}

trainer_state.json

@@ -0,0 +1,130 @@
+{
+  "best_metric": 71.4437,
+  "best_model_checkpoint": "bin/indosum-base-3/checkpoint-4460",
+  "epoch": 5.0,
+  "eval_steps": 500,
+  "global_step": 4460,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
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+      "eval_rouge2": 56.7545,
+      "eval_rougeL": 61.4956,
+      "eval_rougeLsum": 63.81,
+      "eval_runtime": 190.626,
+      "eval_samples_per_second": 3.934,
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+      "eval_rougeLsum": 69.0763,
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+      "eval_samples_per_second": 3.91,
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+      "eval_samples_per_second": 3.974,
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+  "logging_steps": 500,
+  "max_steps": 4460,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 5,
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+  "train_batch_size": 16,
+  "trial_name": null,
+  "trial_params": null
+}