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bart-cnn-samsum-peft

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  1. README.md +17 -12
  2. adapter_model.safetensors +1 -1
  3. runs/Jun06_04-00-34_cced2c94343d/events.out.tfevents.1717646443.cced2c94343d.622.1 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -18,7 +18,7 @@ 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 samsum dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5691
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  ## Model description
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@@ -43,22 +43,27 @@ 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: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 3.1533 | 1.0 | 37 | 2.3528 |
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- | 2.3091 | 2.0 | 74 | 1.6478 |
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- | 1.4519 | 3.0 | 111 | 1.0883 |
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- | 1.0666 | 4.0 | 148 | 0.7953 |
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- | 0.7106 | 5.0 | 185 | 0.6731 |
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- | 0.5671 | 6.0 | 222 | 0.6205 |
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- | 0.5583 | 7.0 | 259 | 0.5940 |
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- | 0.5599 | 8.0 | 296 | 0.5790 |
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- | 0.5602 | 9.0 | 333 | 0.5715 |
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- | 0.5338 | 10.0 | 370 | 0.5691 |
 
 
 
 
 
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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 samsum dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4334
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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: 15
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.4513 | 1.0 | 37 | 0.5301 |
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+ | 0.45 | 2.0 | 74 | 0.5104 |
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+ | 0.4505 | 3.0 | 111 | 0.4969 |
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+ | 0.4882 | 4.0 | 148 | 0.4857 |
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+ | 0.4246 | 5.0 | 185 | 0.4759 |
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+ | 0.386 | 6.0 | 222 | 0.4672 |
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+ | 0.3959 | 7.0 | 259 | 0.4599 |
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+ | 0.4179 | 8.0 | 296 | 0.4536 |
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+ | 0.427 | 9.0 | 333 | 0.4480 |
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+ | 0.3997 | 10.0 | 370 | 0.4435 |
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+ | 0.4041 | 11.0 | 407 | 0.4400 |
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+ | 0.4021 | 12.0 | 444 | 0.4371 |
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+ | 0.3551 | 13.0 | 481 | 0.4351 |
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+ | 0.3619 | 14.0 | 518 | 0.4338 |
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+ | 0.3768 | 15.0 | 555 | 0.4334 |
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  ### Framework versions
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