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ahmedmbutt
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PTS-Bart-Large-CNN

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  1. README.md +17 -51
  2. model.safetensors +1 -1
  3. runs/Jun24_16-23-47_a407000c0675/events.out.tfevents.1719246228.a407000c0675.257.0 +2 -2
README.md CHANGED
@@ -7,41 +7,7 @@ metrics:
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  - rouge
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  model-index:
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  - name: PTS-Bart-Large-CNN
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- results:
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- - task:
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- type: summarization
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- name: Summarization
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- dataset:
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- name: PTS Dataset
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- type: PTS-Dataset
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- metrics:
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- - name: Rouge1
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- type: rouge
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- value: 0.6591
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- - name: Rouge2
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- type: rouge
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- value: 0.449
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- - name: Rougel
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- type: rouge
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- value: 0.5635
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- - name: Rougelsum
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- type: rouge
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- value: 0.5633
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- datasets:
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- - ahmedmbutt/PTS-Dataset
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- language:
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- - en
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- library_name: transformers
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- widget:
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- - text: >-
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- I have to say that I do miss talking to a good psychiatrist- however. I
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- could sit and argue for ages with a psychiatrist who is intelligent and kind
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- (quite hard to find- but they do exist). Especially now that I have a PhD in
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- philosophy and have read everything that can be found on madness- including
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- the notes they wrote about me when I was in the hospital. Nowadays-
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- psychiatrists have a tendency to sign me off pretty quickly when I come onto
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- their radar. They don’t wish to deal with me- I tire them out.
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- pipeline_tag: summarization
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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
@@ -49,14 +15,14 @@ should probably proofread and complete it, then remove this comment. -->
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  # PTS-Bart-Large-CNN
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- This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the PTS dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1442
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- - Rouge1: 0.6591
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- - Rouge2: 0.449
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- - Rougel: 0.5635
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- - Rougelsum: 0.5633
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- - Gen Len: 78.7977
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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- | No log | 1.0 | 220 | 0.8235 | 0.6279 | 0.4019 | 0.5268 | 0.5267 | 82.8295 |
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- | No log | 2.0 | 440 | 0.8053 | 0.6461 | 0.4278 | 0.5486 | 0.5484 | 78.6318 |
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- | 0.7147 | 3.0 | 660 | 0.8889 | 0.6471 | 0.4324 | 0.5491 | 0.5488 | 79.4432 |
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- | 0.7147 | 4.0 | 880 | 0.9679 | 0.6533 | 0.4391 | 0.5538 | 0.5534 | 80.2023 |
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- | 0.2566 | 5.0 | 1100 | 0.9734 | 0.6563 | 0.4422 | 0.5574 | 0.5571 | 78.9727 |
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- | 0.2566 | 6.0 | 1320 | 1.0504 | 0.6538 | 0.4436 | 0.559 | 0.5585 | 78.5682 |
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- | 0.1136 | 7.0 | 1540 | 1.1172 | 0.6591 | 0.4474 | 0.5646 | 0.5647 | 78.6068 |
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- | 0.1136 | 8.0 | 1760 | 1.1442 | 0.6591 | 0.449 | 0.5635 | 0.5633 | 78.7977 |
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  ### Framework versions
@@ -103,4 +69,4 @@ The following hyperparameters were used during training:
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  - Transformers 4.41.2
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  - Pytorch 2.3.0+cu121
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  - Datasets 2.20.0
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- - Tokenizers 0.19.1
 
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  - rouge
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  model-index:
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  - name: PTS-Bart-Large-CNN
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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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  # PTS-Bart-Large-CNN
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+ This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1760
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+ - Rouge1: 0.6551
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+ - Rouge2: 0.4332
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+ - Rougel: 0.5543
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+ - Rougelsum: 0.5541
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+ - Gen Len: 80.0886
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | No log | 1.0 | 220 | 0.8239 | 0.6263 | 0.3973 | 0.5238 | 0.5237 | 84.2023 |
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+ | No log | 2.0 | 440 | 0.8201 | 0.6461 | 0.4184 | 0.5417 | 0.5416 | 81.1659 |
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+ | 0.7121 | 3.0 | 660 | 0.8661 | 0.6479 | 0.4226 | 0.5448 | 0.5454 | 80.5409 |
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+ | 0.7121 | 4.0 | 880 | 0.9784 | 0.6474 | 0.4242 | 0.5424 | 0.5425 | 82.2932 |
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+ | 0.2619 | 5.0 | 1100 | 1.0645 | 0.655 | 0.4327 | 0.5517 | 0.5517 | 80.8386 |
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+ | 0.2619 | 6.0 | 1320 | 1.1098 | 0.6548 | 0.4339 | 0.5542 | 0.5543 | 81.3545 |
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+ | 0.1124 | 7.0 | 1540 | 1.1528 | 0.6528 | 0.4298 | 0.5511 | 0.551 | 80.5705 |
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+ | 0.1124 | 8.0 | 1760 | 1.1760 | 0.6551 | 0.4332 | 0.5543 | 0.5541 | 80.0886 |
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  ### Framework versions
 
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  - Transformers 4.41.2
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  - Pytorch 2.3.0+cu121
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  - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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