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longformer-8bitadam-3072
ajdsouza/longformer-8bitadam-3072
longformer-8bitadam-3072 is a token classification model from ajdsouza. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- longformer
- Access
- Public
- Created
- Mar 19, 2024
- Updated
- Mar 19, 2024
- SHA
- 482d5a21
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Base models
Model card
From the Hugging Face model README
<!-- 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-3072
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: 0.0217
- Recall: 1.0
- Precision: 0.9697
- F1: 0.9988
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 | Recall | Precision | F1 |
|---|---|---|---|---|---|---|
| 0.0057 | 1.0 | 100 | 0.0276 | 1.0 | 0.9412 | 0.9976 |
| 0.0003 | 2.0 | 200 | 0.0217 | 1.0 | 0.9697 | 0.9988 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
- Task
- Token Classification
- Library
- transformers
- Type
- longformer
- License
- apache-2.0
- Created
- Mar 19, 2024
- Updated
- Mar 19, 2024