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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: Longformer-finetuned-comp5
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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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# Longformer-finetuned-comp5
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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: 0.8180
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- Precision: 0.5680
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- Recall: 0.7490
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- F1: 0.6430
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- Accuracy: 0.6430
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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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| 0.8296 | 1.0 | 1012 | 0.5801 | 0.4806 | 0.6633 | 0.5448 | 0.5448 |
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| 0.5367 | 2.0 | 2024 | 0.5386 | 0.5617 | 0.7042 | 0.6172 | 0.6172 |
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| 0.4109 | 3.0 | 3036 | 0.5755 | 0.5590 | 0.7261 | 0.6248 | 0.6248 |
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| 0.3088 | 4.0 | 4048 | 0.6167 | 0.5775 | 0.7394 | 0.6435 | 0.6435 |
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| 0.2234 | 5.0 | 5060 | 0.7098 | 0.5626 | 0.7477 | 0.6370 | 0.6370 |
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| 0.1637 | 6.0 | 6072 | 0.7399 | 0.5742 | 0.7413 | 0.6438 | 0.6438 |
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| 0.1236 | 7.0 | 7084 | 0.8180 | 0.5680 | 0.7490 | 0.6430 | 0.6430 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.10.0+cu111
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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