libeanim
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Commit
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Parent(s):
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add models
Browse files- .gitattributes +1 -0
- README.md +91 -3
- all_results.json +3 -0
- config.json +3 -0
- eval_results.json +3 -0
- model.safetensors +3 -0
- special_tokens_map.json +3 -0
- tokenizer.json +3 -0
- tokenizer_config.json +3 -0
- train_results.json +3 -0
- trainer_state.json +3 -0
- training_args.bin +3 -0
.gitattributes
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README.md
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---
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---
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library_name: transformers
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base_model: cahya/NusaBert-v1.3
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tags:
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- generated_from_trainer
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datasets:
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- grit-id/id_nergrit_corpus
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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: nusabert_nergrit_1.3
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results:
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- task:
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name: Token Classification
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type: token-classification
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dataset:
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name: grit-id/id_nergrit_corpus ner
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type: grit-id/id_nergrit_corpus
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config: ner
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split: validation
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args: ner
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metrics:
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- name: Precision
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type: precision
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value: 0.8010483135824977
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- name: Recall
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type: recall
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value: 0.8338275412169375
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- name: F1
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type: f1
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value: 0.8171093159760562
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- name: Accuracy
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type: accuracy
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value: 0.9476653696498054
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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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# nusabert_nergrit_1.3
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This model is a fine-tuned version of [cahya/NusaBert-v1.3](https://huggingface.co/cahya/NusaBert-v1.3) on the grit-id/id_nergrit_corpus ner dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2174
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- Precision: 0.8010
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- Recall: 0.8338
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- F1: 0.8171
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- Accuracy: 0.9477
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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: 32
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- eval_batch_size: 32
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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- total_train_batch_size: 64
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- total_eval_batch_size: 64
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 3.0
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### Training results
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### Framework versions
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- Transformers 4.49.0
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- Pytorch 2.5.1+cu124
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- Datasets 2.19.2
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- Tokenizers 0.21.0
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all_results.json
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version https://git-lfs.github.com/spec/v1
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size 559
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config.json
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version https://git-lfs.github.com/spec/v1
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size 2643
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eval_results.json
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version https://git-lfs.github.com/spec/v1
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size 346
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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special_tokens_map.json
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version https://git-lfs.github.com/spec/v1
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size 695
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tokenizer.json
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tokenizer_config.json
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version https://git-lfs.github.com/spec/v1
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size 19280
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train_results.json
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trainer_state.json
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version https://git-lfs.github.com/spec/v1
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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size 5368
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