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finetuned-v-1
Abinaya/finetuned-v-1
finetuned-v-1 is a token classification model from Abinaya. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- lilt
- Access
- Public
- Created
- Oct 19, 2024
- Updated
- Oct 19, 2024
- SHA
- 10ed1994
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Base models
Datasets
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. -->
finetuned-v-1
This model is a fine-tuned version of lilt-xlm-roberta-base on the funsd dataset. It achieves the following results on the evaluation set:
- Loss: 1.1752
- Precision: 0.5978
- Recall: 0.5978
- F1: 0.5978
- Accuracy: 0.5978
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: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.3986 | 0.5319 | 100 | 1.1752 | 0.5978 | 0.5978 | 0.5978 | 0.5978 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
- Task
- Token Classification
- Library
- transformers
- Type
- lilt
- Created
- Oct 19, 2024
- Updated
- Oct 19, 2024