End of training
Browse files- README.md +23 -8
- all_results.json +29 -0
- eval_results.json +13 -0
- generated_predictions.txt +0 -0
- predict_results.json +12 -0
- train_results.json +9 -0
- trainer_state.json +130 -0
README.md
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---
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license: apache-2.0
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base_model: LazarusNLP/IndoNanoT5-base
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tags:
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- rouge
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model-index:
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- name: liputan6-seq_bn-rf64
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results:
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# liputan6-seq_bn-rf64
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This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on the id_liputan6 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.
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- Rouge1:
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- Rouge2:
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- Rougel: 21.
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- Rougelsum:
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- Gen Len:
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## Model description
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---
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language:
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- id
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license: apache-2.0
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base_model: LazarusNLP/IndoNanoT5-base
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tags:
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- rouge
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model-index:
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- name: liputan6-seq_bn-rf64
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results:
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- task:
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name: Summarization
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type: summarization
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dataset:
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name: id_liputan6 canonical
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type: id_liputan6
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config: canonical
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split: validation
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args: canonical
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metrics:
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- name: Rouge1
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type: rouge
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value: 25.4752
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# liputan6-seq_bn-rf64
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This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on the id_liputan6 canonical dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.7425
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- Rouge1: 25.4752
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- Rouge2: 11.3075
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- Rougel: 21.8512
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- Rougelsum: 23.007
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- Gen Len: 41.252
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## Model description
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all_results.json
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{
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"epoch": 5.0,
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"eval_rougeL": 21.8512,
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"eval_rougeLsum": 23.007,
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"eval_runtime": 568.6779,
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"eval_samples": 1000,
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"eval_samples_per_second": 1.758,
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"eval_steps_per_second": 0.056,
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"predict_gen_len": 40.157,
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"predict_loss": 2.1879005432128906,
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"predict_rouge1": 32.7565,
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"predict_rouge2": 17.4187,
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"predict_rougeL": 27.8602,
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"predict_rougeLsum": 30.166,
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"predict_runtime": 549.1274,
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"predict_samples": 1000,
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"predict_samples_per_second": 1.821,
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"predict_steps_per_second": 0.058,
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"total_flos": 3430869073920000.0,
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"train_loss": 2.32020258827815,
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"train_runtime": 726.5333,
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"train_samples": 1000,
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"train_samples_per_second": 6.882,
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"train_steps_per_second": 0.434
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}
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eval_results.json
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{
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"epoch": 5.0,
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"eval_gen_len": 41.252,
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"eval_loss": 2.7424604892730713,
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"eval_rouge1": 25.4752,
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"eval_rouge2": 11.3075,
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"eval_rougeL": 21.8512,
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"eval_rougeLsum": 23.007,
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"eval_runtime": 568.6779,
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"eval_samples": 1000,
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"eval_samples_per_second": 1.758,
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"eval_steps_per_second": 0.056
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}
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generated_predictions.txt
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predict_results.json
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{
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"predict_gen_len": 40.157,
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"predict_loss": 2.1879005432128906,
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"predict_rouge1": 32.7565,
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"predict_rouge2": 17.4187,
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"predict_rougeL": 27.8602,
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"predict_rougeLsum": 30.166,
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"predict_runtime": 549.1274,
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"predict_samples": 1000,
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"predict_samples_per_second": 1.821,
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"predict_steps_per_second": 0.058
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}
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train_results.json
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{
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"total_flos": 3430869073920000.0,
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"train_samples_per_second": 6.882,
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"train_steps_per_second": 0.434
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}
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trainer_state.json
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