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mdaffarudiyanto
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t5-small-finetuned-xsum

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End of training

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Files changed (3) hide show
  1. README.md +14 -14
  2. model.safetensors +1 -1
  3. runs/Dec19_08-57-22_fb888c7c5d85/events.out.tfevents.1702976251.fb888c7c5d85.805.1 +2 -2
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Rouge1
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  type: rouge
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- value: 29.6441
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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
@@ -32,12 +32,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.3880
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- - Rouge1: 29.6441
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- - Rouge2: 8.7669
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- - Rougel: 23.5197
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- - Rougelsum: 23.5219
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- - Gen Len: 18.8262
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  ## Model description
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@@ -56,7 +56,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
@@ -67,16 +67,16 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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- |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
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- | 2.6699 | 1.0 | 12753 | 2.4405 | 28.7816 | 8.0799 | 22.7002 | 22.6944 | 18.8276 |
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- | 2.609 | 2.0 | 25506 | 2.4003 | 29.4687 | 8.5602 | 23.3411 | 23.3422 | 18.8076 |
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- | 2.598 | 3.0 | 38259 | 2.3880 | 29.6441 | 8.7669 | 23.5197 | 23.5219 | 18.8262 |
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  ### Framework versions
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  - Transformers 4.35.2
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- - Pytorch 2.1.0+cu118
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  - Datasets 2.15.0
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  - Tokenizers 0.15.0
 
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  metrics:
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  - name: Rouge1
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  type: rouge
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+ value: 31.4321
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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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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.2343
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+ - Rouge1: 31.4321
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+ - Rouge2: 10.1196
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+ - Rougel: 25.036
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+ - Rougelsum: 25.0332
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+ - Gen Len: 18.8159
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
 
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
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+ | 2.5218 | 1.0 | 12753 | 2.3041 | 30.5945 | 9.5092 | 24.3364 | 24.3414 | 18.8252 |
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+ | 2.4327 | 2.0 | 25506 | 2.2534 | 31.1591 | 9.9687 | 24.8258 | 24.8257 | 18.7936 |
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+ | 2.3953 | 3.0 | 38259 | 2.2343 | 31.4321 | 10.1196 | 25.036 | 25.0332 | 18.8159 |
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  ### Framework versions
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  - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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  - Datasets 2.15.0
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  - Tokenizers 0.15.0
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