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---
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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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- f1
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- accuracy
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model-index:
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- name: Bert_v5
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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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# Bert_v5
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This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9191
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- Precision: 0.7612
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- Recall: 0.8007
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- F1: 0.5106
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- Accuracy: 0.7357
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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: 5e-05
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 8
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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: 0.1
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- num_epochs: 7
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 1.0663 | 1.0 | 934 | 0.8636 | 0.6973 | 0.8467 | 0.4082 | 0.7023 |
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| 0.8354 | 2.0 | 1868 | 0.8261 | 0.7367 | 0.8086 | 0.4733 | 0.7221 |
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| 0.7164 | 3.0 | 2802 | 0.7737 | 0.7572 | 0.7988 | 0.5055 | 0.7347 |
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| 0.6149 | 4.0 | 3736 | 0.7542 | 0.7488 | 0.8402 | 0.5176 | 0.7438 |
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| 0.5153 | 5.0 | 4670 | 0.8185 | 0.7614 | 0.8123 | 0.5017 | 0.7389 |
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| 0.4314 | 6.0 | 5604 | 0.8599 | 0.7543 | 0.8259 | 0.5085 | 0.7395 |
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| 0.3689 | 7.0 | 6538 | 0.9191 | 0.7612 | 0.8007 | 0.5106 | 0.7357 |
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.10.0+cu111
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- Datasets 2.1.0
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- Tokenizers 0.12.1
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