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ahmedmbutt
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PTS-Bart-Large-CNN

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Transformers
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English
bart
text2text-generation
Generated from Trainer
Eval Results
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End of training

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  1. README.md +15 -11
  2. model.safetensors +1 -1
  3. runs/Jun15_11-27-20_4441297fbb55/events.out.tfevents.1718450841.4441297fbb55.7613.0 +2 -2
README.md CHANGED
@@ -17,12 +17,12 @@ should probably proofread and complete it, then remove this comment. -->
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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: 1.0177
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- - Rouge1: 0.6339
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- - Rouge2: 0.4113
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- - Rougel: 0.5344
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- - Rougelsum: 0.5338
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- - Gen Len: 76.1278
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  ## Model description
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@@ -47,17 +47,21 @@ The following hyperparameters were used during training:
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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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- - num_epochs: 4
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  - mixed_precision_training: Native AMP
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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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- | No log | 1.0 | 180 | 0.9026 | 0.6109 | 0.3819 | 0.5098 | 0.5094 | 76.9722 |
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- | No log | 2.0 | 360 | 0.9012 | 0.6273 | 0.4054 | 0.5285 | 0.5284 | 76.3833 |
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- | 0.6717 | 3.0 | 540 | 0.9357 | 0.6312 | 0.4071 | 0.5297 | 0.5295 | 76.25 |
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- | 0.6717 | 4.0 | 720 | 1.0177 | 0.6339 | 0.4113 | 0.5344 | 0.5338 | 76.1278 |
 
 
 
 
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  ### Framework versions
 
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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: 1.2638
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+ - Rouge1: 0.6376
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+ - Rouge2: 0.4143
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+ - Rougel: 0.538
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+ - Rougelsum: 0.5387
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+ - Gen Len: 76.8417
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  ## Model description
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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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+ - num_epochs: 8
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  - mixed_precision_training: Native AMP
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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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+ | No log | 1.0 | 180 | 0.8748 | 0.6166 | 0.3827 | 0.5058 | 0.5055 | 77.6583 |
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+ | No log | 2.0 | 360 | 0.8774 | 0.6307 | 0.4064 | 0.5302 | 0.531 | 77.5111 |
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+ | 0.6761 | 3.0 | 540 | 0.9064 | 0.635 | 0.4052 | 0.5309 | 0.5311 | 76.2833 |
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+ | 0.6761 | 4.0 | 720 | 1.0386 | 0.6329 | 0.4038 | 0.5261 | 0.5262 | 78.4889 |
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+ | 0.6761 | 5.0 | 900 | 1.0993 | 0.6285 | 0.4016 | 0.5239 | 0.5246 | 77.0083 |
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+ | 0.2016 | 6.0 | 1080 | 1.2025 | 0.6351 | 0.4126 | 0.5351 | 0.5356 | 76.0722 |
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+ | 0.2016 | 7.0 | 1260 | 1.2399 | 0.6356 | 0.4108 | 0.5362 | 0.5368 | 78.5361 |
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+ | 0.2016 | 8.0 | 1440 | 1.2638 | 0.6376 | 0.4143 | 0.538 | 0.5387 | 76.8417 |
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  ### Framework versions
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