Model save

README.md

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+---
+license: mit
+base_model: gogamza/kobart-summarization
+tags:
+- generated_from_trainer
+model-index:
+- name: summary2
+  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. -->
+
+# summary2
+
+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: 0.3377
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|
+| 1.5089        | 1.23  | 500  | 0.3360          |
+| 0.238         | 2.47  | 1000 | 0.3377          |
+| 0.1456        | 3.7   | 1500 | 0.3513          |
+| 0.0848        | 4.94  | 2000 | 0.3753          |
+| 0.0482        | 6.17  | 2500 | 0.4024          |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.0+cu121
+- Datasets 2.18.0
+- 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": "4.39.3"
+}

model.safetensors

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