Training complete

README.md

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+---
+license: mit
+base_model: october-sd/mbart-large-50-finetuned-mr-sum
+tags:
+- summarization
+- generated_from_trainer
+model-index:
+- name: mbart-large-50-finetuned-mr-sum-finetuned-hindi
+ 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-finetuned-mr-sum-finetuned-hindi
+
+This model is a fine-tuned version of [october-sd/mbart-large-50-finetuned-mr-sum](https://huggingface.co/october-sd/mbart-large-50-finetuned-mr-sum) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.9019
+
+## 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: 5.6e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 300
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 2.281 | 1.0 | 3905 | 1.9741 |
+| 1.6731 | 2.0 | 7810 | 1.9019 |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

generation_config.json

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+ "early_stopping": true,
+ "eos_token_id": 2,
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+ "max_length": 200,
+ "num_beams": 5,
+ "pad_token_id": 1,
+ "transformers_version": "4.39.3"
+}

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