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End of training
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README.md
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---
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license: other
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library_name: peft
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tags:
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- generated_from_trainer
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datasets:
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- glue
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metrics:
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- accuracy
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base_model: facebook/opt-350m
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model-index:
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- name: opt-350m-vanilla_finetuning_with_lora-mnli-mm-d1_fs2
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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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# opt-350m-vanilla_finetuning_with_lora-mnli-mm-d1_fs2
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This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9078
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- Accuracy: 0.5293
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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: 2e-06
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- train_batch_size: 16
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- eval_batch_size: 16
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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: 5
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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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| 0.4435 | 1.0 | 1 | 0.9079 | 0.5290 |
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| 0.5839 | 2.0 | 2 | 0.9078 | 0.5293 |
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| 0.5077 | 3.0 | 3 | 0.9078 | 0.5292 |
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| 0.5722 | 4.0 | 4 | 0.9077 | 0.5292 |
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| 0.6715 | 5.0 | 5 | 0.9077 | 0.5293 |
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### Framework versions
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- PEFT 0.7.1.dev0
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- Transformers 4.36.0.dev0
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- Pytorch 2.1.0+cu118
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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