Model save
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README.md
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---
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base_model: castorini/afriteva_v2_base
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library_name: peft
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license: apache-2.0
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metrics:
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- accuracy
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tags:
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- generated_from_trainer
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model-index:
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- name: cross_amh
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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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# cross_amh
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This model is a fine-tuned version of [castorini/afriteva_v2_base](https://huggingface.co/castorini/afriteva_v2_base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7276
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- Model Preparation Time: 0.0061
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- Accuracy: {'accuracy': 0.18509375}
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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: 0.0003
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- train_batch_size: 64
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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: 15
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy |
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|:-------------:|:-------:|:-----:|:---------------:|:----------------------:|:-------------------------:|
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| 1.4008 | 2.2173 | 5000 | 1.0351 | 0.0061 | {'accuracy': 0.17328125} |
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| 1.0872 | 4.4346 | 10000 | 0.8747 | 0.0061 | {'accuracy': 0.17896875} |
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| 0.9522 | 6.6519 | 15000 | 0.8086 | 0.0061 | {'accuracy': 0.18146875} |
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| 0.8673 | 8.8692 | 20000 | 0.7648 | 0.0061 | {'accuracy': 0.183390625} |
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| 0.7922 | 11.0865 | 25000 | 0.7456 | 0.0061 | {'accuracy': 0.184375} |
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| 0.7608 | 13.3038 | 30000 | 0.7276 | 0.0061 | {'accuracy': 0.18509375} |
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### Framework versions
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- PEFT 0.7.1
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- Transformers 4.43.3
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- Pytorch 2.4.0+cu121
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- Datasets 2.15.0
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- Tokenizers 0.19.1
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