End of training

README.md

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+---
+license: cc-by-4.0
+library_name: peft
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+base_model: deepset/roberta-base-squad2
+model-index:
+- name: STS-Lora-Fine-Tuning-Capstone-roberta-base-deepset-test-111-with-higher-r-mid
+  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. -->
+
+# STS-Lora-Fine-Tuning-Capstone-roberta-base-deepset-test-111-with-higher-r-mid
+
+This model is a fine-tuned version of [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0593
+- Accuracy: 0.5627
+
+## 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: 3e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 297  | 1.2901          | 0.4489   |
+| 1.2919        | 2.0   | 594  | 1.1817          | 0.4931   |
+| 1.2919        | 3.0   | 891  | 1.1639          | 0.4996   |
+| 1.0546        | 4.0   | 1188 | 1.1222          | 0.5221   |
+| 1.0546        | 5.0   | 1485 | 1.1199          | 0.5279   |
+| 0.9971        | 6.0   | 1782 | 1.1256          | 0.5257   |
+| 0.9606        | 7.0   | 2079 | 1.0944          | 0.5439   |
+| 0.9606        | 8.0   | 2376 | 1.1414          | 0.5323   |
+| 0.9423        | 9.0   | 2673 | 1.0932          | 0.5337   |
+| 0.9423        | 10.0  | 2970 | 1.1029          | 0.5468   |
+| 0.9171        | 11.0  | 3267 | 1.0914          | 0.5330   |
+| 0.9069        | 12.0  | 3564 | 1.0582          | 0.5533   |
+| 0.9069        | 13.0  | 3861 | 1.0677          | 0.5526   |
+| 0.8954        | 14.0  | 4158 | 1.0817          | 0.5460   |
+| 0.8954        | 15.0  | 4455 | 1.0703          | 0.5526   |
+| 0.8926        | 16.0  | 4752 | 1.0724          | 0.5555   |
+| 0.8845        | 17.0  | 5049 | 1.0583          | 0.5591   |
+| 0.8845        | 18.0  | 5346 | 1.0749          | 0.5620   |
+| 0.8666        | 19.0  | 5643 | 1.0559          | 0.5518   |
+| 0.8666        | 20.0  | 5940 | 1.0660          | 0.5591   |
+| 0.8602        | 21.0  | 6237 | 1.0620          | 0.5533   |
+| 0.8582        | 22.0  | 6534 | 1.0891          | 0.5591   |
+| 0.8582        | 23.0  | 6831 | 1.0565          | 0.5656   |
+| 0.8539        | 24.0  | 7128 | 1.0680          | 0.5591   |
+| 0.8539        | 25.0  | 7425 | 1.0556          | 0.5620   |
+| 0.8551        | 26.0  | 7722 | 1.0605          | 0.5569   |
+| 0.8512        | 27.0  | 8019 | 1.0560          | 0.5635   |
+| 0.8512        | 28.0  | 8316 | 1.0552          | 0.5627   |
+| 0.8505        | 29.0  | 8613 | 1.0599          | 0.5613   |
+| 0.8505        | 30.0  | 8910 | 1.0593          | 0.5627   |
+
+
+### Framework versions
+
+- PEFT 0.10.0
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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