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pegasus-large-finetuned-cnn_dailymail

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  1. README.md +19 -19
  2. model.safetensors +1 -1
  3. runs/May11_17-56-50_DESKTOP-I570M0U/events.out.tfevents.1715439423.DESKTOP-I570M0U.5347.2 +2 -2
README.md CHANGED
@@ -16,17 +16,17 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8591
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- - Rouge1: 47.5545
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- - Rouge2: 24.7124
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- - Rougel: 34.1029
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- - Rougelsum: 44.0189
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- - Bleu 1: 37.0636
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- - Bleu 2: 25.5604
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- - Bleu 3: 19.3415
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- - Meteor: 38.0261
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- - Lungime rezumat: 57.9183
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- - Lungime original: 48.6393
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5.6e-05
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- - train_batch_size: 2
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- - eval_batch_size: 2
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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 results
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- | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu 1 | Bleu 2 | Bleu 3 | Meteor | Lungime rezumat | Lungime original |
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- |:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:---------------:|:----------------:|
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- | 0.9693 | 1.0 | 28660 | 0.8691 | 47.0692 | 24.3586 | 33.6526 | 43.4825 | 36.2858 | 24.9738 | 18.8926 | 37.8237 | 59.475 | 48.6393 |
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- | 0.8248 | 2.0 | 57320 | 0.8598 | 46.751 | 24.0748 | 33.3009 | 43.1207 | 36.0845 | 24.7477 | 18.6962 | 37.8529 | 60.7557 | 48.6393 |
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- | 0.7578 | 3.0 | 85980 | 0.8570 | 47.2636 | 24.4414 | 33.8604 | 43.6832 | 36.6893 | 25.2309 | 19.0981 | 38.0561 | 59.0953 | 48.6393 |
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- | 0.7145 | 4.0 | 114640 | 0.8591 | 47.5545 | 24.7124 | 34.1029 | 44.0189 | 37.0636 | 25.5604 | 19.3415 | 38.0261 | 57.9183 | 48.6393 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0469
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+ - Rouge1: 45.2373
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+ - Rouge2: 22.4813
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+ - Rougel: 31.8329
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+ - Rougelsum: 41.6862
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+ - Bleu 1: 34.8304
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+ - Bleu 2: 23.4162
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+ - Bleu 3: 17.4357
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+ - Meteor: 35.0815
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+ - Lungime rezumat: 56.5898
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+ - Lungime original: 48.7656
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5.6e-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 results
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu 1 | Bleu 2 | Bleu 3 | Meteor | Lungime rezumat | Lungime original |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:---------------:|:----------------:|
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+ | 1.2058 | 1.0 | 7165 | 1.0640 | 44.5245 | 22.1439 | 31.4275 | 40.9808 | 33.9802 | 22.8183 | 16.9712 | 34.1035 | 55.245 | 48.7656 |
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+ | 1.0602 | 2.0 | 14330 | 1.0534 | 44.7088 | 22.1286 | 31.3398 | 41.0804 | 34.1571 | 22.9231 | 17.0479 | 35.1782 | 59.6166 | 48.7656 |
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+ | 1.0144 | 3.0 | 21495 | 1.0479 | 45.0257 | 22.3325 | 31.7313 | 41.4189 | 34.6084 | 23.227 | 17.2859 | 34.7757 | 56.1443 | 48.7656 |
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+ | 0.9875 | 4.0 | 28660 | 1.0469 | 45.2373 | 22.4813 | 31.8329 | 41.6862 | 34.8304 | 23.4162 | 17.4357 | 35.0815 | 56.5898 | 48.7656 |
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  ### Framework versions
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