Dagobert42
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Push distilbert-base-uncased trained on biored-original_splits.pt
Browse files- README.md +84 -0
- config.json +42 -0
- model.safetensors +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +56 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
README.md
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---
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language:
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- en
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license: mit
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base_model: distilbert-base-uncased
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tags:
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- low-resource NER
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- token_classification
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- biomedicine
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- medical NER
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- generated_from_trainer
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datasets:
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- medicine
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metrics:
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- accuracy
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- precision
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- recall
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- f1
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model-index:
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- name: Dagobert42/distilbert-base-uncased-biored-finetuned
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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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# Dagobert42/distilbert-base-uncased-biored-finetuned
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the bigbio/biored dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6976
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- Accuracy: 0.7703
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- Precision: 0.5335
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- Recall: 0.424
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- F1: 0.4652
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- Weighted F1: 0.7512
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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-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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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: 50
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Weighted F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------:|
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| No log | 1.0 | 25 | 0.9181 | 0.7144 | 0.4183 | 0.1593 | 0.151 | 0.6108 |
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| No log | 2.0 | 50 | 0.8580 | 0.7283 | 0.5273 | 0.2252 | 0.2508 | 0.6404 |
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| No log | 3.0 | 75 | 0.8232 | 0.7369 | 0.5603 | 0.2769 | 0.3173 | 0.6638 |
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| No log | 4.0 | 100 | 0.7814 | 0.7476 | 0.5184 | 0.3618 | 0.4085 | 0.7031 |
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| No log | 5.0 | 125 | 0.7691 | 0.7507 | 0.5306 | 0.3929 | 0.4283 | 0.7173 |
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| No log | 6.0 | 150 | 0.7492 | 0.7607 | 0.5494 | 0.3919 | 0.4396 | 0.7244 |
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| No log | 7.0 | 175 | 0.7616 | 0.7622 | 0.5553 | 0.4048 | 0.4481 | 0.728 |
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| No log | 8.0 | 200 | 0.7256 | 0.7657 | 0.5437 | 0.4306 | 0.4717 | 0.7426 |
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| No log | 9.0 | 225 | 0.7413 | 0.7684 | 0.5565 | 0.4315 | 0.4739 | 0.7422 |
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| No log | 10.0 | 250 | 0.7497 | 0.7721 | 0.5606 | 0.4364 | 0.4789 | 0.7446 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.0.1+cu117
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- Datasets 2.12.0
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- Tokenizers 0.15.0
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config.json
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{
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"_name_or_path": "distilbert-base-uncased",
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"activation": "gelu",
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"architectures": [
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"DistilBertForTokenClassification"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "null",
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"1": "GeneOrGeneProduct",
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"2": "DiseaseOrPhenotypicFeature",
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"3": "ChemicalEntity",
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"4": "OrganismTaxon",
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"5": "SequenceVariant",
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"6": "CellLine"
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},
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"initializer_range": 0.02,
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"label2id": {
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"CellLine": 6,
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"ChemicalEntity": 3,
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"DiseaseOrPhenotypicFeature": 2,
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"GeneOrGeneProduct": 1,
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"OrganismTaxon": 4,
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"SequenceVariant": 5,
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"null": 0
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"n_heads": 12,
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"n_layers": 6,
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"pad_token_id": 0,
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.35.2",
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"vocab_size": 30522
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:a6b77f92470c32771073dc6fedf9dbaacabb338a841291109a831d0eaffcb1d5
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size 265485396
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special_tokens_map.json
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{
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"cls_token": "[CLS]",
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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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tokenizer.json
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tokenizer_config.json
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{
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"add_prefix_space": true,
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"added_tokens_decoder": {
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"0": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"100": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"101": {
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"102": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"103": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "DistilBertTokenizer",
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"unk_token": "[UNK]"
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:f1eac4aea06037b9c3183adcbf333a38e173e27a040d33ef7a4a7a2239a5e1a4
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size 4219
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vocab.txt
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