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LEDv3_ACLsum_all_aspects

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End of training

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  1. README.md +25 -20
  2. model.safetensors +1 -1
  3. runs/Jul08_12-15-25_tardis/events.out.tfevents.1751969726.tardis.16633.0 +3 -0
  4. runs/Jul08_12-17-37_tardis/events.out.tfevents.1751969858.tardis.16793.0 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -22,21 +22,21 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.8523
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- - Rouge1: 0.306
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- - Rouge2: 0.1081
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- - Rougel: 0.2447
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- - Rougelsum: 0.2447
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- - Gen Len: 20.8533
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- - Bleu: 0.05
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- - Precisions: 0.1248
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- - Brevity Penalty: 0.6089
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- - Length Ratio: 0.6684
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- - Translation Length: 2407.0
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  - Reference Length: 3601.0
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- - Precision: 0.8812
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- - Recall: 0.8701
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- - F1: 0.8756
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  - Hashcode: roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1)
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  ## Model description
@@ -64,17 +64,22 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 16
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Bleu | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Precision | Recall | F1 | Hashcode |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|:----------:|:---------------:|:------------:|:------------------:|:----------------:|:---------:|:------:|:------:|:---------------------------------------------------------:|
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- | No log | 1.0 | 19 | 4.1851 | 0.2835 | 0.088 | 0.2261 | 0.2267 | 20.6467 | 0.04 | 0.108 | 0.6311 | 0.6848 | 2466.0 | 3601.0 | 0.8845 | 0.8678 | 0.876 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
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- | No log | 2.0 | 38 | 3.2829 | 0.2809 | 0.0891 | 0.2258 | 0.2252 | 20.64 | 0.041 | 0.1083 | 0.6093 | 0.6687 | 2408.0 | 3601.0 | 0.8795 | 0.8661 | 0.8726 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
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- | No log | 3.0 | 57 | 3.0226 | 0.2883 | 0.096 | 0.2293 | 0.2302 | 20.7867 | 0.0454 | 0.1151 | 0.6093 | 0.6687 | 2408.0 | 3601.0 | 0.88 | 0.8682 | 0.874 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
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- | No log | 4.0 | 76 | 2.8930 | 0.301 | 0.1068 | 0.2374 | 0.2371 | 20.78 | 0.049 | 0.1246 | 0.6017 | 0.6631 | 2388.0 | 3601.0 | 0.8817 | 0.8699 | 0.8757 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
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- | No log | 5.0 | 95 | 2.8523 | 0.306 | 0.1081 | 0.2447 | 0.2447 | 20.8533 | 0.05 | 0.1248 | 0.6089 | 0.6684 | 2407.0 | 3601.0 | 0.8812 | 0.8701 | 0.8756 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.2405
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+ - Rouge1: 0.3564
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+ - Rouge2: 0.1444
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+ - Rougel: 0.296
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+ - Rougelsum: 0.2951
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+ - Gen Len: 20.96
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+ - Bleu: 0.0646
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+ - Precisions: 0.1586
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+ - Brevity Penalty: 0.5945
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+ - Length Ratio: 0.6579
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+ - Translation Length: 2369.0
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  - Reference Length: 3601.0
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+ - Precision: 0.892
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+ - Recall: 0.8776
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+ - F1: 0.8846
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  - Hashcode: roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1)
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  ## Model description
 
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  - total_train_batch_size: 16
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Bleu | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Precision | Recall | F1 | Hashcode |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|:----------:|:---------------:|:------------:|:------------------:|:----------------:|:---------:|:------:|:------:|:---------------------------------------------------------:|
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+ | No log | 1.0 | 19 | 4.0849 | 0.2835 | 0.0826 | 0.2239 | 0.2243 | 20.5333 | 0.0374 | 0.105 | 0.6263 | 0.6812 | 2453.0 | 3601.0 | 0.8837 | 0.8674 | 0.8754 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
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+ | No log | 2.0 | 38 | 3.1922 | 0.2787 | 0.0853 | 0.2229 | 0.2223 | 20.7667 | 0.0396 | 0.1061 | 0.6161 | 0.6737 | 2426.0 | 3601.0 | 0.8767 | 0.8646 | 0.8705 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
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+ | No log | 3.0 | 57 | 2.8716 | 0.292 | 0.098 | 0.2328 | 0.2329 | 20.84 | 0.0461 | 0.1181 | 0.6082 | 0.6679 | 2405.0 | 3601.0 | 0.8812 | 0.8688 | 0.8749 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
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+ | No log | 4.0 | 76 | 2.6529 | 0.3166 | 0.1192 | 0.2573 | 0.2566 | 20.92 | 0.0576 | 0.1366 | 0.6104 | 0.6695 | 2411.0 | 3601.0 | 0.8861 | 0.8725 | 0.8792 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
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+ | No log | 5.0 | 95 | 2.5101 | 0.3441 | 0.1353 | 0.282 | 0.2813 | 20.94 | 0.0613 | 0.1495 | 0.593 | 0.6568 | 2365.0 | 3601.0 | 0.8895 | 0.8763 | 0.8828 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
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+ | No log | 6.0 | 114 | 2.3985 | 0.3501 | 0.1415 | 0.2909 | 0.2912 | 20.92 | 0.0616 | 0.1514 | 0.5983 | 0.6606 | 2379.0 | 3601.0 | 0.8913 | 0.8771 | 0.884 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
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+ | No log | 7.0 | 133 | 2.3215 | 0.3557 | 0.1398 | 0.295 | 0.2949 | 20.9667 | 0.0608 | 0.1545 | 0.593 | 0.6568 | 2365.0 | 3601.0 | 0.8919 | 0.8775 | 0.8846 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
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+ | No log | 8.0 | 152 | 2.2783 | 0.3494 | 0.1417 | 0.2922 | 0.2918 | 20.9333 | 0.0637 | 0.1561 | 0.588 | 0.6532 | 2352.0 | 3601.0 | 0.8907 | 0.8769 | 0.8837 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
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+ | No log | 9.0 | 171 | 2.2467 | 0.3566 | 0.145 | 0.297 | 0.2968 | 20.96 | 0.0649 | 0.1591 | 0.5926 | 0.6565 | 2364.0 | 3601.0 | 0.8921 | 0.8775 | 0.8846 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
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+ | No log | 10.0 | 190 | 2.2405 | 0.3564 | 0.1444 | 0.296 | 0.2951 | 20.96 | 0.0646 | 0.1586 | 0.5945 | 0.6579 | 2369.0 | 3601.0 | 0.892 | 0.8776 | 0.8846 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
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  ### Framework versions
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