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led-large-16384-cnn_dailymail

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End of training

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Files changed (3) hide show
  1. README.md +30 -26
  2. generation_config.json +5 -1
  3. pytorch_model.bin +1 -1
README.md CHANGED
@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Rouge1
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  type: rouge
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- value: 0.38124598557029016
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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
@@ -31,11 +31,11 @@ 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 the cnn_dailymail dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6312
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- - Rouge1: 0.3812
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- - Rouge2: 0.1691
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- - Rougel: 0.2544
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- - Rougelsum: 0.3599
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  ## Model description
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@@ -66,26 +66,30 @@ 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 |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
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- | 1.9531 | 0.4 | 500 | 1.8639 | 0.3485 | 0.1441 | 0.2275 | 0.3288 |
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- | 1.9563 | 0.8 | 1000 | 1.8260 | 0.3538 | 0.1482 | 0.2315 | 0.3343 |
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- | 1.7176 | 1.2 | 1500 | 1.8208 | 0.3628 | 0.1527 | 0.2383 | 0.3433 |
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- | 1.7197 | 1.6 | 2000 | 1.8162 | 0.3696 | 0.1602 | 0.2434 | 0.3486 |
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- | 1.8086 | 2.0 | 2500 | 1.7924 | 0.3558 | 0.1533 | 0.2334 | 0.3361 |
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- | 1.2448 | 2.4 | 3000 | 1.8510 | 0.3703 | 0.1591 | 0.2447 | 0.3483 |
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- | 1.3574 | 2.8 | 3500 | 1.8277 | 0.3741 | 0.1593 | 0.2422 | 0.3540 |
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- | 1.0966 | 3.2 | 4000 | 1.8924 | 0.3682 | 0.1576 | 0.2424 | 0.3479 |
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- | 0.9938 | 3.6 | 4500 | 1.8957 | 0.3723 | 0.1599 | 0.2451 | 0.3511 |
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- | 1.0735 | 4.0 | 5000 | 1.8772 | 0.3653 | 0.1557 | 0.2399 | 0.3454 |
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- | 0.9106 | 4.4 | 5500 | 1.9401 | 0.3720 | 0.1585 | 0.2436 | 0.3504 |
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- | 1.015 | 4.8 | 6000 | 1.9320 | 0.3725 | 0.1570 | 0.2429 | 0.3515 |
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- | 1.7854 | 0.36 | 6500 | 1.7800 | 0.3624 | 0.1544 | 0.2390 | 0.3422 |
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- | 1.9079 | 0.39 | 7000 | 1.7629 | 0.3573 | 0.1553 | 0.2352 | 0.3370 |
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- | 1.7606 | 3.34 | 7500 | 1.6902 | 0.3783 | 0.1673 | 0.2521 | 0.3570 |
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- | 1.7571 | 3.57 | 8000 | 1.6563 | 0.3802 | 0.1691 | 0.2538 | 0.3587 |
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- | 1.6602 | 3.79 | 8500 | 1.6439 | 0.3814 | 0.1693 | 0.2548 | 0.3600 |
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- | 1.6614 | 4.01 | 9000 | 1.6312 | 0.3812 | 0.1691 | 0.2544 | 0.3599 |
 
 
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Rouge1
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  type: rouge
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+ value: 0.38275620598885174
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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 [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the cnn_dailymail dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.6093
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+ - Rouge1: 0.3828
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+ - Rouge2: 0.1701
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+ - Rougel: 0.2561
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+ - Rougelsum: 0.3613
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
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+ | 1.9531 | 0.4 | 500 | 1.8639 | 0.3485 | 0.1441 | 0.2275 | 0.3288 |
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+ | 1.9563 | 0.8 | 1000 | 1.8260 | 0.3538 | 0.1482 | 0.2315 | 0.3343 |
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+ | 1.7176 | 1.2 | 1500 | 1.8208 | 0.3628 | 0.1527 | 0.2383 | 0.3433 |
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+ | 1.7197 | 1.6 | 2000 | 1.8162 | 0.3696 | 0.1602 | 0.2434 | 0.3486 |
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+ | 1.8086 | 2.0 | 2500 | 1.7924 | 0.3558 | 0.1533 | 0.2334 | 0.3361 |
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+ | 1.2448 | 2.4 | 3000 | 1.8510 | 0.3703 | 0.1591 | 0.2447 | 0.3483 |
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+ | 1.3574 | 2.8 | 3500 | 1.8277 | 0.3741 | 0.1593 | 0.2422 | 0.3540 |
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+ | 1.0966 | 3.2 | 4000 | 1.8924 | 0.3682 | 0.1576 | 0.2424 | 0.3479 |
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+ | 0.9938 | 3.6 | 4500 | 1.8957 | 0.3723 | 0.1599 | 0.2451 | 0.3511 |
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+ | 1.0735 | 4.0 | 5000 | 1.8772 | 0.3653 | 0.1557 | 0.2399 | 0.3454 |
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+ | 0.9106 | 4.4 | 5500 | 1.9401 | 0.3720 | 0.1585 | 0.2436 | 0.3504 |
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+ | 1.015 | 4.8 | 6000 | 1.9320 | 0.3725 | 0.1570 | 0.2429 | 0.3515 |
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+ | 1.7854 | 0.36 | 6500 | 1.7800 | 0.3624 | 0.1544 | 0.2390 | 0.3422 |
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+ | 1.9079 | 0.39 | 7000 | 1.7629 | 0.3573 | 0.1553 | 0.2352 | 0.3370 |
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+ | 1.7606 | 3.34 | 7500 | 1.6902 | 0.3783 | 0.1673 | 0.2521 | 0.3570 |
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+ | 1.7571 | 3.57 | 8000 | 1.6563 | 0.3802 | 0.1691 | 0.2538 | 0.3587 |
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+ | 1.6602 | 3.79 | 8500 | 1.6439 | 0.3814 | 0.1693 | 0.2548 | 0.3600 |
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+ | 1.6614 | 4.01 | 9000 | 1.6312 | 0.3812 | 0.1691 | 0.2544 | 0.3599 |
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+ | 1.668 | 4.24 | 9500 | 1.6189 | 0.3815 | 0.1689 | 0.2550 | 0.3603 |
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+ | 1.6491 | 4.46 | 10000 | 1.6172 | 0.3799 | 0.1681 | 0.2540 | 0.3586 |
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+ | 1.5994 | 4.68 | 10500 | 1.6132 | 0.3825 | 0.1702 | 0.2560 | 0.3610 |
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+ | 1.6493 | 4.9 | 11000 | 1.6093 | 0.3828 | 0.1701 | 0.2561 | 0.3613 |
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  ### Framework versions
generation_config.json CHANGED
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  {
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- "_from_model_config": true,
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  "bos_token_id": 0,
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  "decoder_start_token_id": 2,
 
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  "pad_token_id": 1,
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  "transformers_version": "4.30.2"
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  }
 
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  "bos_token_id": 0,
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  "decoder_start_token_id": 2,
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+ "early_stopping": true,
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+ "length_penalty": 2.0,
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+ "max_length": 1024,
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+ "min_length": 100,
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+ "no_repeat_ngram_size": 3,
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  "pad_token_id": 1,
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  "transformers_version": "4.30.2"
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