End of training

README.md

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+---
+base_model: facebook/mbart-large-50
+library_name: peft
+license: mit
+tags:
+- generated_from_trainer
+model-index:
+- name: mbart-large-50_Nepali_News_Summarization_QLoRA_4bit
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# mbart-large-50_Nepali_News_Summarization_QLoRA_4bit
+
+This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3739
+- Rouge-1 R: 0.3816
+- Rouge-1 P: 0.389
+- Rouge-1 F: 0.3751
+- Rouge-2 R: 0.2142
+- Rouge-2 P: 0.2189
+- Rouge-2 F: 0.2093
+- Rouge-l R: 0.3711
+- Rouge-l P: 0.3779
+- Rouge-l F: 0.3646
+- Gen Len: 14.1121
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0005
+- train_batch_size: 5
+- eval_batch_size: 5
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Rouge-1 R | Rouge-1 P | Rouge-1 F | Rouge-2 R | Rouge-2 P | Rouge-2 F | Rouge-l R | Rouge-l P | Rouge-l F | Gen Len |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:---------:|:---------:|:---------:|:---------:|:---------:|:---------:|:---------:|:---------:|:-------:|
+| 1.5617        | 1.0   | 10191 | 1.4589          | 0.3552    | 0.3834    | 0.3572    | 0.1923    | 0.21      | 0.1926    | 0.3456    | 0.3728    | 0.3474    | 13.6645 |
+| 1.42          | 2.0   | 20382 | 1.3993          | 0.3674    | 0.3858    | 0.3661    | 0.2047    | 0.2159    | 0.2029    | 0.3581    | 0.3758    | 0.3568    | 13.7819 |
+| 1.2407        | 3.0   | 30573 | 1.3739          | 0.3816    | 0.389     | 0.3751    | 0.2142    | 0.2189    | 0.2093    | 0.3711    | 0.3779    | 0.3646    | 14.1121 |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.42.3
+- Pytorch 2.1.2
+- Datasets 2.20.0
+- Tokenizers 0.19.1

runs/Jul21_02-10-53_48c211bedb36/events.out.tfevents.1721527855.48c211bedb36.24.0

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