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flan-t5-small-lamp-4u-finetuned-3

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  1. README.md +32 -30
  2. model.safetensors +1 -1
README.md CHANGED
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  ---
 
 
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  tags:
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  - generated_from_trainer
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  metrics:
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  - rouge
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  model-index:
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- - name: flan-t5-base-lamp-7t-finetuned-1
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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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  should probably proofread and complete it, then remove this comment. -->
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- # flan-t5-base-lamp-7t-finetuned-1
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- This model was trained from scratch on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2121
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- - Rouge1: 0.5299
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- - Rouge2: 0.2730
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- - Rougel: 0.4776
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- - Rougelsum: 0.4930
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  ## Model description
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@@ -39,8 +41,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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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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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
@@ -51,26 +53,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
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- | 7.0613 | 1.0 | 840 | 1.2605 | 0.5053 | 0.2462 | 0.4513 | 0.4657 |
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- | 1.3665 | 2.0 | 1680 | 1.2271 | 0.5124 | 0.2562 | 0.4600 | 0.4747 |
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- | 1.3009 | 3.0 | 2520 | 1.2114 | 0.5179 | 0.2613 | 0.4652 | 0.4802 |
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- | 1.2594 | 4.0 | 3360 | 1.2039 | 0.5229 | 0.2656 | 0.4677 | 0.4839 |
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- | 1.227 | 5.0 | 4200 | 1.1988 | 0.5247 | 0.2669 | 0.4698 | 0.4860 |
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- | 1.1918 | 6.0 | 5040 | 1.1966 | 0.5238 | 0.2698 | 0.4701 | 0.4860 |
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- | 1.1696 | 7.0 | 5880 | 1.1934 | 0.5261 | 0.2702 | 0.4723 | 0.4880 |
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- | 1.1285 | 8.0 | 6720 | 1.1933 | 0.5237 | 0.2693 | 0.4701 | 0.4849 |
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- | 1.1153 | 9.0 | 7560 | 1.1961 | 0.5263 | 0.2708 | 0.4724 | 0.4880 |
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- | 1.0927 | 10.0 | 8400 | 1.1961 | 0.5254 | 0.2691 | 0.4720 | 0.4874 |
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- | 1.0661 | 11.0 | 9240 | 1.2010 | 0.5234 | 0.2684 | 0.4698 | 0.4854 |
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- | 1.0634 | 12.0 | 10080 | 1.2003 | 0.5259 | 0.2723 | 0.4729 | 0.4885 |
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- | 1.046 | 13.0 | 10920 | 1.2019 | 0.5277 | 0.2726 | 0.4747 | 0.4907 |
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- | 1.0273 | 14.0 | 11760 | 1.2045 | 0.5309 | 0.2749 | 0.4776 | 0.4940 |
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- | 1.0218 | 15.0 | 12600 | 1.2077 | 0.5295 | 0.2728 | 0.4771 | 0.4925 |
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- | 1.0208 | 16.0 | 13440 | 1.2095 | 0.5303 | 0.2728 | 0.4775 | 0.4928 |
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- | 1.003 | 17.0 | 14280 | 1.2110 | 0.5301 | 0.2726 | 0.4772 | 0.4929 |
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- | 1.003 | 18.0 | 15120 | 1.2099 | 0.5314 | 0.2729 | 0.4781 | 0.4941 |
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- | 0.9893 | 19.0 | 15960 | 1.2115 | 0.5302 | 0.2737 | 0.4779 | 0.4933 |
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- | 0.9918 | 20.0 | 16800 | 1.2121 | 0.5299 | 0.2730 | 0.4776 | 0.4930 |
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  ### Framework versions
 
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  ---
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+ license: apache-2.0
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+ base_model: google/flan-t5-small
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  tags:
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  - generated_from_trainer
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  metrics:
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  - rouge
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  model-index:
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+ - name: flan-t5-small-lamp-4u-finetuned-3
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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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  should probably proofread and complete it, then remove this comment. -->
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+ # flan-t5-small-lamp-4u-finetuned-3
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+ This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.4088
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+ - Rouge1: 0.1634
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+ - Rouge2: 0.0510
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+ - Rougel: 0.1494
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+ - Rougelsum: 0.1500
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
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+ | 2.6388 | 1.0 | 1566 | 2.5235 | 0.1413 | 0.0452 | 0.1311 | 0.1316 |
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+ | 2.5039 | 2.0 | 3132 | 2.4539 | 0.1469 | 0.0474 | 0.1354 | 0.1359 |
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+ | 2.401 | 3.0 | 4698 | 2.4320 | 0.1525 | 0.0486 | 0.1409 | 0.1414 |
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+ | 2.3748 | 4.0 | 6264 | 2.4193 | 0.1528 | 0.0495 | 0.1414 | 0.1417 |
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+ | 2.2997 | 5.0 | 7830 | 2.4120 | 0.1559 | 0.0490 | 0.1427 | 0.1430 |
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+ | 2.2742 | 6.0 | 9396 | 2.4042 | 0.1562 | 0.0508 | 0.1436 | 0.1438 |
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+ | 2.2404 | 7.0 | 10962 | 2.4039 | 0.1584 | 0.0515 | 0.1457 | 0.1461 |
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+ | 2.2249 | 8.0 | 12528 | 2.4010 | 0.1624 | 0.0509 | 0.1491 | 0.1495 |
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+ | 2.1985 | 9.0 | 14094 | 2.3993 | 0.1622 | 0.0520 | 0.1493 | 0.1501 |
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+ | 2.1509 | 10.0 | 15660 | 2.3993 | 0.1599 | 0.0505 | 0.1454 | 0.1462 |
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+ | 2.1226 | 11.0 | 17226 | 2.4026 | 0.1631 | 0.0519 | 0.1498 | 0.1503 |
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+ | 2.107 | 12.0 | 18792 | 2.4040 | 0.1623 | 0.0513 | 0.1487 | 0.1491 |
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+ | 2.0855 | 13.0 | 20358 | 2.4049 | 0.1634 | 0.0517 | 0.1493 | 0.1498 |
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+ | 2.0678 | 14.0 | 21924 | 2.4028 | 0.1631 | 0.0515 | 0.1489 | 0.1495 |
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+ | 2.0899 | 15.0 | 23490 | 2.4052 | 0.1628 | 0.0510 | 0.1489 | 0.1496 |
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+ | 2.0777 | 16.0 | 25056 | 2.4050 | 0.1628 | 0.0503 | 0.1493 | 0.1498 |
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+ | 2.0572 | 17.0 | 26622 | 2.4076 | 0.1620 | 0.0511 | 0.1481 | 0.1488 |
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+ | 2.0408 | 18.0 | 28188 | 2.4066 | 0.1625 | 0.0510 | 0.1487 | 0.1495 |
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+ | 2.0538 | 19.0 | 29754 | 2.4076 | 0.1635 | 0.0510 | 0.1496 | 0.1503 |
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+ | 2.0283 | 20.0 | 31320 | 2.4088 | 0.1634 | 0.0510 | 0.1494 | 0.1500 |
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  ### Framework versions
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