christinacdl
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End of training
Browse files- README.md +73 -0
- added_tokens.json +3 -0
- logs/events.out.tfevents.1687468337.e3b85aa49c5f.5566.0 +2 -2
- pytorch_model.bin +1 -1
- special_tokens_map.json +9 -0
- spm.model +3 -0
- tokenizer_config.json +16 -0
README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: clickbait_binary_detection_DeBERTa
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results: []
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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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# clickbait_binary_detection_DeBERTa
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This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7269
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- Macro F1: 0.9010
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- Micro F1: 0.9069
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- Accuracy: 0.9069
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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: 2e-06
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Micro F1 | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:--------:|
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| 0.2692 | 1.0 | 5475 | 0.2676 | 0.9051 | 0.9142 | 0.9142 |
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| 0.2492 | 2.0 | 10951 | 0.3331 | 0.9078 | 0.9156 | 0.9156 |
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| 0.2189 | 3.0 | 16426 | 0.3909 | 0.9107 | 0.9169 | 0.9169 |
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| 0.1769 | 4.0 | 21902 | 0.3799 | 0.9114 | 0.9178 | 0.9178 |
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| 0.1479 | 5.0 | 27377 | 0.5103 | 0.8980 | 0.9032 | 0.9032 |
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| 0.108 | 6.0 | 32853 | 0.5215 | 0.9123 | 0.9183 | 0.9183 |
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| 0.0957 | 7.0 | 38328 | 0.6549 | 0.8974 | 0.9028 | 0.9028 |
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| 0.0773 | 8.0 | 43804 | 0.6768 | 0.9044 | 0.9101 | 0.9101 |
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| 0.0586 | 9.0 | 49279 | 0.6837 | 0.9023 | 0.9083 | 0.9083 |
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| 0.0439 | 10.0 | 54750 | 0.7269 | 0.9010 | 0.9069 | 0.9069 |
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### Framework versions
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- Transformers 4.27.1
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- Pytorch 2.0.1+cu118
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- Datasets 2.9.0
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- Tokenizers 0.13.3
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added_tokens.json
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{
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"[MASK]": 128000
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}
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logs/events.out.tfevents.1687468337.e3b85aa49c5f.5566.0
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size 26325
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pytorch_model.bin
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size 1740396281
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special_tokens_map.json
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{
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"bos_token": "[CLS]",
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"cls_token": "[CLS]",
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"eos_token": "[SEP]",
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"mask_token": "[MASK]",
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"unk_token": "[UNK]"
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}
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spm.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:c679fbf93643d19aab7ee10c0b99e460bdbc02fedf34b92b05af343b4af586fd
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size 2464616
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tokenizer_config.json
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{
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"bos_token": "[CLS]",
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"eos_token": "[SEP]",
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"mask_token": "[MASK]",
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"sp_model_kwargs": {},
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"special_tokens_map_file": null,
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"split_by_punct": false,
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"tokenizer_class": "DebertaV2Tokenizer",
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"unk_token": "[UNK]",
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"vocab_type": "spm"
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}
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