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-filtered-120-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-filtered-120-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: 0.7040
+- Accuracy: 0.6854
+
+## 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: 64
+- eval_batch_size: 64
+- 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   | 57   | 1.0545          | 0.4551   |
+| No log        | 2.0   | 114  | 1.0270          | 0.5      |
+| No log        | 3.0   | 171  | 0.9823          | 0.5262   |
+| No log        | 4.0   | 228  | 0.9416          | 0.5356   |
+| No log        | 5.0   | 285  | 0.8917          | 0.5805   |
+| No log        | 6.0   | 342  | 0.7931          | 0.6180   |
+| No log        | 7.0   | 399  | 0.7627          | 0.6423   |
+| No log        | 8.0   | 456  | 0.7679          | 0.6573   |
+| 0.7963        | 9.0   | 513  | 0.7380          | 0.6610   |
+| 0.7963        | 10.0  | 570  | 0.7256          | 0.6760   |
+| 0.7963        | 11.0  | 627  | 0.7223          | 0.6742   |
+| 0.7963        | 12.0  | 684  | 0.7255          | 0.6779   |
+| 0.7963        | 13.0  | 741  | 0.7132          | 0.6779   |
+| 0.7963        | 14.0  | 798  | 0.7097          | 0.6835   |
+| 0.7963        | 15.0  | 855  | 0.7116          | 0.6760   |
+| 0.7963        | 16.0  | 912  | 0.7200          | 0.6760   |
+| 0.7963        | 17.0  | 969  | 0.7176          | 0.6760   |
+| 0.615         | 18.0  | 1026 | 0.7133          | 0.6798   |
+| 0.615         | 19.0  | 1083 | 0.7121          | 0.6798   |
+| 0.615         | 20.0  | 1140 | 0.7117          | 0.6873   |
+| 0.615         | 21.0  | 1197 | 0.7028          | 0.6816   |
+| 0.615         | 22.0  | 1254 | 0.7033          | 0.6854   |
+| 0.615         | 23.0  | 1311 | 0.7054          | 0.6798   |
+| 0.615         | 24.0  | 1368 | 0.7059          | 0.6854   |
+| 0.615         | 25.0  | 1425 | 0.6996          | 0.6835   |
+| 0.615         | 26.0  | 1482 | 0.7045          | 0.6835   |
+| 0.5826        | 27.0  | 1539 | 0.7032          | 0.6854   |
+| 0.5826        | 28.0  | 1596 | 0.7030          | 0.6854   |
+| 0.5826        | 29.0  | 1653 | 0.7046          | 0.6854   |
+| 0.5826        | 30.0  | 1710 | 0.7040          | 0.6854   |
+
+
+### 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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