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README.md
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---
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library_name: transformers
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base_model: microsoft/infoxlm-base
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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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- f1
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- precision
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- recall
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model-index:
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- name: vp-infoxlm-base-dsc
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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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# vp-infoxlm-base-dsc
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This model is a fine-tuned version of [microsoft/infoxlm-base](https://huggingface.co/microsoft/infoxlm-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4642
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- Accuracy: 0.8251
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- F1: 0.8249
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- Precision: 0.8259
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- Recall: 0.8251
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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: 1e-05
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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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- lr_scheduler_warmup_ratio: 0.05
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.9971 | 1.0 | 1590 | 0.8708 | 0.5664 | 0.5565 | 0.6042 | 0.5664 |
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| 0.7175 | 2.0 | 3180 | 0.5943 | 0.7631 | 0.7626 | 0.7713 | 0.7631 |
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| 0.5942 | 3.0 | 4770 | 0.5007 | 0.8069 | 0.8069 | 0.8075 | 0.8069 |
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| 0.4981 | 4.0 | 6360 | 0.4676 | 0.8188 | 0.8182 | 0.8218 | 0.8188 |
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| 0.4669 | 5.0 | 7950 | 0.4642 | 0.8251 | 0.8249 | 0.8259 | 0.8251 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.0
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- Datasets 3.0.0
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- Tokenizers 0.19.1
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