End of training

README.md

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+---
+license: mit
+base_model: gogamza/kobart-base-v2
+tags:
+- generated_from_trainer
+model-index:
+- name: KoBART_base_v2-trial
+  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. -->
+
+# KoBART_base_v2-trial
+
+This model is a fine-tuned version of [gogamza/kobart-base-v2](https://huggingface.co/gogamza/kobart-base-v2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1815
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 20
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 2.4147        | 0.11  | 50   | 0.5490          |
+| 0.5457        | 0.22  | 100  | 0.4810          |
+| 0.4642        | 0.32  | 150  | 0.3971          |
+| 0.4364        | 0.43  | 200  | 0.3955          |
+| 0.4111        | 0.54  | 250  | 0.3851          |
+| 0.3888        | 0.65  | 300  | 0.3438          |
+| 0.3586        | 0.76  | 350  | 0.3290          |
+| 0.3304        | 0.87  | 400  | 0.3201          |
+| 0.3337        | 0.97  | 450  | 0.2992          |
+| 0.2677        | 1.08  | 500  | 0.3161          |
+| 0.2576        | 1.19  | 550  | 0.2981          |
+| 0.2467        | 1.3   | 600  | 0.2846          |
+| 0.2369        | 1.41  | 650  | 0.2674          |
+| 0.226         | 1.52  | 700  | 0.2529          |
+| 0.2204        | 1.62  | 750  | 0.2446          |
+| 0.204         | 1.73  | 800  | 0.2400          |
+| 0.2071        | 1.84  | 850  | 0.2262          |
+| 0.1911        | 1.95  | 900  | 0.2153          |
+| 0.1591        | 2.06  | 950  | 0.2121          |
+| 0.1338        | 2.16  | 1000 | 0.2090          |
+| 0.1312        | 2.27  | 1050 | 0.1986          |
+| 0.1336        | 2.38  | 1100 | 0.1947          |
+| 0.1205        | 2.49  | 1150 | 0.1903          |
+| 0.1162        | 2.6   | 1200 | 0.1867          |
+| 0.1187        | 2.71  | 1250 | 0.1840          |
+| 0.1171        | 2.81  | 1300 | 0.1821          |
+| 0.1149        | 2.92  | 1350 | 0.1815          |
+
+
+### Framework versions
+
+- Transformers 4.36.0
+- Pytorch 2.0.1+cu117
+- Datasets 2.15.0
+- Tokenizers 0.15.0

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "decoder_start_token_id": 1,
+  "eos_token_id": 1,
+  "forced_eos_token_id": 1,
+  "pad_token_id": 3,
+  "transformers_version": "4.36.0"
+}

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runs/Dec19_11-09-00_e64a5fb166fb/events.out.tfevents.1702951741.e64a5fb166fb.8679.1

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