End of training

README.md

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+---
+license: mit
+library_name: peft
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+base_model: microsoft/deberta-v3-xsmall
+model-index:
+- name: STS-Lora-Fine-Tuning-Capstone-Deberta-old-model-pipe-test_augmentation
+  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-Deberta-old-model-pipe-test_augmentation
+
+This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2431
+- Accuracy: 0.4627
+
+## 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: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 360  | 1.7500          | 0.2429   |
+| 1.7474        | 2.0   | 720  | 1.7255          | 0.2451   |
+| 1.681         | 3.0   | 1080 | 1.6291          | 0.3332   |
+| 1.681         | 4.0   | 1440 | 1.4764          | 0.4130   |
+| 1.5419        | 5.0   | 1800 | 1.4165          | 0.4159   |
+| 1.4014        | 6.0   | 2160 | 1.3548          | 0.4336   |
+| 1.3269        | 7.0   | 2520 | 1.3122          | 0.4456   |
+| 1.3269        | 8.0   | 2880 | 1.3003          | 0.4529   |
+| 1.2821        | 9.0   | 3240 | 1.2830          | 0.4572   |
+| 1.2516        | 10.0  | 3600 | 1.2757          | 0.4576   |
+| 1.2516        | 11.0  | 3960 | 1.2619          | 0.4590   |
+| 1.2304        | 12.0  | 4320 | 1.2501          | 0.4670   |
+| 1.2172        | 13.0  | 4680 | 1.2674          | 0.4583   |
+| 1.2043        | 14.0  | 5040 | 1.2459          | 0.4656   |
+| 1.2043        | 15.0  | 5400 | 1.2464          | 0.4627   |
+| 1.1956        | 16.0  | 5760 | 1.2439          | 0.4645   |
+| 1.1814        | 17.0  | 6120 | 1.2395          | 0.4648   |
+| 1.1814        | 18.0  | 6480 | 1.2429          | 0.4637   |
+| 1.1816        | 19.0  | 6840 | 1.2450          | 0.4634   |
+| 1.1794        | 20.0  | 7200 | 1.2431          | 0.4627   |
+
+
+### 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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