End of training
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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-
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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model-index:
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- name: vp-infoxlm-
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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-
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This model is a fine-tuned version of [microsoft/infoxlm-
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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- F1: 0.
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- Precision: 0.
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- Recall: 0.
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## Model description
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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:
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- eval_batch_size:
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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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### Training results
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| Training Loss | Epoch | Step
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### Framework versions
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---
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library_name: transformers
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base_model: microsoft/infoxlm-large
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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model-index:
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- name: vp-infoxlm-large-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-large-dsc
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This model is a fine-tuned version of [microsoft/infoxlm-large](https://huggingface.co/microsoft/infoxlm-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6113
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- Accuracy: 0.8706
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- F1: 0.8705
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- Precision: 0.8713
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- Recall: 0.8706
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## Model description
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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: 8
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- eval_batch_size: 4
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.8771 | 1.0 | 3180 | 0.8099 | 0.6890 | 0.6914 | 0.7003 | 0.6890 |
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| 0.5911 | 2.0 | 6360 | 0.5717 | 0.8014 | 0.8007 | 0.8107 | 0.8014 |
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| 0.4608 | 3.0 | 9540 | 0.5323 | 0.8442 | 0.8442 | 0.8449 | 0.8442 |
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| 0.407 | 4.0 | 12720 | 0.5047 | 0.8680 | 0.8679 | 0.8683 | 0.8680 |
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| 0.3372 | 5.0 | 15900 | 0.6113 | 0.8706 | 0.8705 | 0.8713 | 0.8706 |
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### Framework versions
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model.safetensors
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