metadata
license: apache-2.0
base_model: allenai/longformer-base-4096
tags:
- generated_from_trainer
model-index:
- name: output
results: []
output
This model is a fine-tuned version of allenai/longformer-base-4096 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0554
- Name Student Precision: 0.9535
- Name Student Recall: 1.0
- Name Student F1: 0.9762
- Name Student Number: 41
- Url Personal Precision: 0.0
- Url Personal Recall: 0.0
- Url Personal F1: 0.0
- Url Personal Number: 1
- Overall Precision: 0.9535
- Overall Recall: 0.9762
- Overall F1: 0.9647
- Overall Accuracy: 0.9925
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: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Name Student Precision | Name Student Recall | Name Student F1 | Name Student Number | Url Personal Precision | Url Personal Recall | Url Personal F1 | Url Personal Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0023 | 1.0 | 100 | 0.0549 | 0.9535 | 1.0 | 0.9762 | 41 | 0.0 | 0.0 | 0.0 | 1 | 0.9535 | 0.9762 | 0.9647 | 0.9925 |
| 0.0009 | 2.0 | 200 | 0.0554 | 0.9535 | 1.0 | 0.9762 | 41 | 0.0 | 0.0 | 0.0 | 1 | 0.9535 | 0.9762 | 0.9647 | 0.9925 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2