End of training

README.md

@@ -7,41 +7,7 @@ metrics:
 - rouge
 model-index:
 - name: PTS-Bart-Large-CNN
-  results:
-  - task:
-      type: summarization
-      name: Summarization
-    dataset:
-      name: PTS Dataset
-      type: PTS-Dataset
-    metrics:
-    - name: Rouge1
-      type: rouge
-      value: 0.6591
-    - name: Rouge2
-      type: rouge
-      value: 0.449
-    - name: Rougel
-      type: rouge
-      value: 0.5635
-    - name: Rougelsum
-      type: rouge
-      value: 0.5633
-datasets:
-- ahmedmbutt/PTS-Dataset
-language:
-- en
-library_name: transformers
-widget:
-- text: >-
-    I have to say that I do miss talking to a good psychiatrist- however. I
-    could sit and argue for ages with a psychiatrist who is intelligent and kind
-    (quite hard to find- but they do exist). Especially now that I have a PhD in
-    philosophy and have read everything that can be found on madness- including
-    the notes they wrote about me when I was in the hospital. Nowadays-
-    psychiatrists have a tendency to sign me off pretty quickly when I come onto
-    their radar. They don’t wish to deal with me- I tire them out.
-pipeline_tag: summarization
+  results: []
 ---
 
 <!-- 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. -->
 
 # PTS-Bart-Large-CNN
 
-This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the PTS dataset.
+This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.1442
-- Rouge1: 0.6591
-- Rouge2: 0.449
-- Rougel: 0.5635
-- Rougelsum: 0.5633
-- Gen Len: 78.7977
+- Loss: 1.1760
+- Rouge1: 0.6551
+- Rouge2: 0.4332
+- Rougel: 0.5543
+- Rougelsum: 0.5541
+- Gen Len: 80.0886
 
 ## Model description
 
@@ -88,14 +54,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
-| No log        | 1.0   | 220  | 0.8235          | 0.6279 | 0.4019 | 0.5268 | 0.5267    | 82.8295 |
-| No log        | 2.0   | 440  | 0.8053          | 0.6461 | 0.4278 | 0.5486 | 0.5484    | 78.6318 |
-| 0.7147        | 3.0   | 660  | 0.8889          | 0.6471 | 0.4324 | 0.5491 | 0.5488    | 79.4432 |
-| 0.7147        | 4.0   | 880  | 0.9679          | 0.6533 | 0.4391 | 0.5538 | 0.5534    | 80.2023 |
-| 0.2566        | 5.0   | 1100 | 0.9734          | 0.6563 | 0.4422 | 0.5574 | 0.5571    | 78.9727 |
-| 0.2566        | 6.0   | 1320 | 1.0504          | 0.6538 | 0.4436 | 0.559  | 0.5585    | 78.5682 |
-| 0.1136        | 7.0   | 1540 | 1.1172          | 0.6591 | 0.4474 | 0.5646 | 0.5647    | 78.6068 |
-| 0.1136        | 8.0   | 1760 | 1.1442          | 0.6591 | 0.449  | 0.5635 | 0.5633    | 78.7977 |
+| No log        | 1.0   | 220  | 0.8239          | 0.6263 | 0.3973 | 0.5238 | 0.5237    | 84.2023 |
+| No log        | 2.0   | 440  | 0.8201          | 0.6461 | 0.4184 | 0.5417 | 0.5416    | 81.1659 |
+| 0.7121        | 3.0   | 660  | 0.8661          | 0.6479 | 0.4226 | 0.5448 | 0.5454    | 80.5409 |
+| 0.7121        | 4.0   | 880  | 0.9784          | 0.6474 | 0.4242 | 0.5424 | 0.5425    | 82.2932 |
+| 0.2619        | 5.0   | 1100 | 1.0645          | 0.655  | 0.4327 | 0.5517 | 0.5517    | 80.8386 |
+| 0.2619        | 6.0   | 1320 | 1.1098          | 0.6548 | 0.4339 | 0.5542 | 0.5543    | 81.3545 |
+| 0.1124        | 7.0   | 1540 | 1.1528          | 0.6528 | 0.4298 | 0.5511 | 0.551     | 80.5705 |
+| 0.1124        | 8.0   | 1760 | 1.1760          | 0.6551 | 0.4332 | 0.5543 | 0.5541    | 80.0886 |
 
 
 ### Framework versions
@@ -103,4 +69,4 @@ The following hyperparameters were used during training:
 - Transformers 4.41.2
 - Pytorch 2.3.0+cu121
 - Datasets 2.20.0
-- Tokenizers 0.19.1
+- Tokenizers 0.19.1

model.safetensors

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runs/Jun24_16-23-47_a407000c0675/events.out.tfevents.1719246228.a407000c0675.257.0

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