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longt5_xl_sfd_bp_40

Text2Text Generation
Transformers
PyTorch
Safetensors
longt5
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +29 -49
  2. generation_config.json +2 -1
  3. model-00001-of-00003.safetensors +3 -0
  4. model-00002-of-00003.safetensors +3 -0
  5. model-00003-of-00003.safetensors +3 -0
  6. model.safetensors.index.json +590 -0
README.md CHANGED
@@ -1,24 +1,9 @@
1
  ---
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- base_model: /exports/eddie/scratch/s1970716/models/summarization/longt5_xl_sfd_bp_20/checkpoint-280
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  tags:
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  - generated_from_trainer
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- datasets:
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- - learn3r/summ_screen_fd_bp
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- metrics:
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- - rouge
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  model-index:
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  - name: longt5_xl_sfd_bp_40
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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: learn3r/summ_screen_fd_bp
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- type: learn3r/summ_screen_fd_bp
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- metrics:
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- - name: Rouge1
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- type: rouge
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- value: 40.6965
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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
@@ -26,14 +11,9 @@ should probably proofread and complete it, then remove this comment. -->
26
 
27
  # longt5_xl_sfd_bp_40
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- This model is a fine-tuned version of [/exports/eddie/scratch/s1970716/models/summarization/longt5_xl_sfd_bp_20/checkpoint-280](https://huggingface.co//exports/eddie/scratch/s1970716/models/summarization/longt5_xl_sfd_bp_20/checkpoint-280) on the learn3r/summ_screen_fd_bp dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.8277
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- - Rouge1: 40.6965
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- - Rouge2: 17.2793
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- - Rougel: 27.8429
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- - Rougelsum: 39.0726
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- - Gen Len: 294.0890
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  ## Model description
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@@ -64,33 +44,33 @@ 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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- | 0.1033 | 0.97 | 14 | 3.1096 | 40.3355 | 16.0557 | 27.4642 | 38.6436 | 279.7507 |
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- | 0.0836 | 1.95 | 28 | 3.0361 | 38.2411 | 16.5448 | 26.6409 | 36.5841 | 368.4659 |
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- | 0.0717 | 2.99 | 43 | 2.9389 | 32.0114 | 13.7953 | 22.278 | 30.726 | 489.2047 |
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- | 0.0614 | 3.97 | 57 | 3.0221 | 32.969 | 13.7053 | 22.7428 | 31.6951 | 477.7240 |
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- | 0.1275 | 4.94 | 71 | 2.8277 | 40.6965 | 17.2793 | 27.8429 | 39.0726 | 294.0890 |
74
- | 0.0511 | 5.98 | 86 | 3.0433 | 33.6479 | 15.0729 | 23.5443 | 32.3304 | 476.8457 |
75
- | 0.0666 | 6.96 | 100 | 3.1150 | 37.743 | 16.2368 | 26.2524 | 36.1313 | 390.4362 |
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- | 0.0398 | 8.0 | 115 | 3.2225 | 41.3177 | 16.6663 | 28.7806 | 39.5914 | 203.4006 |
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- | 0.0396 | 8.97 | 129 | 3.1462 | 39.9605 | 16.6732 | 28.3459 | 38.226 | 123.8309 |
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- | 0.0466 | 9.95 | 143 | 3.2545 | 40.7977 | 16.9616 | 27.427 | 38.8973 | 298.5579 |
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- | 0.043 | 10.99 | 158 | 3.3188 | 36.6349 | 16.1781 | 25.1327 | 35.1793 | 425.1395 |
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- | 0.0538 | 11.97 | 172 | 2.8277 | 36.7878 | 15.1186 | 24.9774 | 35.275 | 394.8605 |
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- | 0.028 | 12.94 | 186 | 3.4398 | 42.9644 | 18.1812 | 29.1539 | 41.0465 | 188.1780 |
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- | 0.1056 | 13.98 | 201 | 3.3348 | 41.1626 | 17.1605 | 27.6558 | 39.2548 | 261.2967 |
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- | 0.0303 | 14.96 | 215 | 3.0238 | 42.2372 | 17.7292 | 28.8099 | 40.3325 | 231.6083 |
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- | 0.0234 | 16.0 | 230 | 3.3485 | 41.714 | 17.7161 | 27.9345 | 39.8519 | 306.1602 |
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- | 0.0263 | 16.97 | 244 | 3.2419 | 42.0014 | 17.2719 | 28.499 | 40.2024 | 210.7122 |
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- | 0.0225 | 17.95 | 258 | 3.3453 | 41.7766 | 17.7154 | 28.4692 | 39.9749 | 248.5786 |
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- | 0.0225 | 18.99 | 273 | 3.4441 | 42.1727 | 17.598 | 28.5122 | 40.4005 | 248.6380 |
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- | 0.0211 | 19.48 | 280 | 3.3211 | 42.5239 | 17.4102 | 28.6868 | 40.6537 | 200.3798 |
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  ### Framework versions
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- - Transformers 4.34.1
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- - Pytorch 2.1.0+cu121
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- - Datasets 2.14.5
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- - Tokenizers 0.14.1
 
1
  ---
 
2
  tags:
3
  - generated_from_trainer
 
 
 
 
4
  model-index:
5
  - name: longt5_xl_sfd_bp_40
6
+ results: []
 
 
 
 
 
 
 
 
 
 
7
  ---
8
 
9
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
11
 
12
  # longt5_xl_sfd_bp_40
13
 
14
+ This model was trained from scratch on an unknown dataset.
15
  It achieves the following results on the evaluation set:
16
+ - Loss: 3.3318
 
 
 
 
 
17
 
18
  ## Model description
19
 
 
44
 
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss |
48
+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.1033 | 0.97 | 14 | 3.1040 |
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+ | 0.0836 | 1.95 | 28 | 3.0540 |
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+ | 0.0717 | 2.99 | 43 | 2.9414 |
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+ | 0.0614 | 3.97 | 57 | 3.0238 |
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+ | 0.1275 | 4.94 | 71 | 2.8326 |
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+ | 0.0511 | 5.98 | 86 | 3.0479 |
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+ | 0.0666 | 6.96 | 100 | 3.1255 |
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+ | 0.0398 | 8.0 | 115 | 3.2240 |
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+ | 0.0396 | 8.97 | 129 | 3.1667 |
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+ | 0.0466 | 9.95 | 143 | 3.2775 |
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+ | 0.043 | 10.99 | 158 | 3.3289 |
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+ | 0.0538 | 11.97 | 172 | 2.8202 |
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+ | 0.028 | 12.94 | 186 | 3.4366 |
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+ | 0.1056 | 13.98 | 201 | 3.3447 |
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+ | 0.0303 | 14.96 | 215 | 3.0069 |
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+ | 0.0234 | 16.0 | 230 | 3.3524 |
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+ | 0.0263 | 16.97 | 244 | 3.2473 |
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+ | 0.0225 | 17.95 | 258 | 3.3365 |
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+ | 0.0225 | 18.99 | 273 | 3.4389 |
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+ | 0.0211 | 19.48 | 280 | 3.3318 |
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  ### Framework versions
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+ - Transformers 4.36.2
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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