End of training
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README.md
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---
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license: apache-2.0
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library_name: peft
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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base_model: albert-base-v2
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model-index:
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- name: NLI-Lora-Fine-Tuning-10K
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# NLI-Lora-Fine-Tuning-10K
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This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8405
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- Accuracy: 0.6071
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 312 | 1.0533 | 0.4667 |
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| 1.0642 | 2.0 | 624 | 1.0234 | 0.5033 |
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| 1.0642 | 3.0 | 936 | 0.9616 | 0.5467 |
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| 1.0052 | 4.0 | 1248 | 0.9010 | 0.5795 |
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| 0.9162 | 5.0 | 1560 | 0.8750 | 0.5876 |
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| 0.9162 | 6.0 | 1872 | 0.8606 | 0.5959 |
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| 0.8817 | 7.0 | 2184 | 0.8512 | 0.6019 |
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| 0.8817 | 8.0 | 2496 | 0.8452 | 0.6051 |
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| 0.8618 | 9.0 | 2808 | 0.8416 | 0.6071 |
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| 0.8551 | 10.0 | 3120 | 0.8405 | 0.6071 |
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### Framework versions
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- PEFT 0.9.0
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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