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---
license: apache-2.0
base_model: allenai/longformer-base-4096
tags:
- generated_from_trainer
metrics:
- recall
- precision
model-index:
- name: longformer-8bitadam-2048-main
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# longformer-8bitadam-2048-main
This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0103
- Recall: 0.9643
- Precision: 0.9643
- F5: 0.9643
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Recall | Precision | F5 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
| 0.0015 | 1.0 | 100 | 0.0197 | 1.0 | 0.9032 | 0.9959 |
| 0.0012 | 2.0 | 200 | 0.0179 | 0.9643 | 0.9643 | 0.9643 |
| 0.0008 | 3.0 | 300 | 0.0103 | 0.9643 | 0.9643 | 0.9643 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
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