Model save

README.md

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+---
+license: mit
+base_model: gogamza/kobart-summarization
+tags:
+- generated_from_trainer
+model-index:
+- name: summary
+  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. -->
+
+# summary
+
+This model is a fine-tuned version of [gogamza/kobart-summarization](https://huggingface.co/gogamza/kobart-summarization) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3757
+
+## 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: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 1.4823        | 1.42  | 500  | 0.3805          |
+| 0.2472        | 2.85  | 1000 | 0.3757          |
+| 0.1306        | 4.27  | 1500 | 0.4135          |
+| 0.0718        | 5.7   | 2000 | 0.4368          |
+| 0.0421        | 7.12  | 2500 | 0.4518          |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.2+cu118
+- Datasets 2.16.1
+- Tokenizers 0.15.0

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "decoder_start_token_id": 2,
+  "eos_token_id": 1,
+  "forced_eos_token_id": 2,
+  "pad_token_id": 3,
+  "transformers_version": "4.37.2"
+}

model.safetensors

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