Push google/mobilebert-uncased trained on biored-original_splits.pt

README.md

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+---
+language:
+- en
+license: mit
+base_model: mobilebert-uncased
+tags:
+- low-resource NER
+- token_classification
+- biomedicine
+- medical NER
+- generated_from_trainer
+datasets:
+- medicine
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: Dagobert42/mobilebert-uncased-biored-finetuned
+ results: []
+---
+
+<!-- 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. -->
+
+# Dagobert42/mobilebert-uncased-biored-finetuned
+
+This model is a fine-tuned version of [mobilebert-uncased](https://huggingface.co/mobilebert-uncased) on the bigbio/biored dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7686
+- Accuracy: 0.7387
+- Precision: 0.2041
+- Recall: 0.2219
+- F1: 0.1908
+- Weighted F1: 0.683
+
+## 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: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Weighted F1 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------:|
+| No log | 1.0 | 25 | 1.2311 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
+| No log | 2.0 | 50 | 1.0356 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
+| No log | 3.0 | 75 | 1.0300 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
+| No log | 4.0 | 100 | 1.0246 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
+| No log | 5.0 | 125 | 1.0162 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
+| No log | 6.0 | 150 | 1.0039 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
+| No log | 7.0 | 175 | 0.9806 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
+| No log | 8.0 | 200 | 0.9148 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
+| No log | 9.0 | 225 | 0.8715 | 0.7187 | 0.2116 | 0.1604 | 0.1484 | 0.6172 |
+| No log | 10.0 | 250 | 0.8303 | 0.7261 | 0.1555 | 0.1972 | 0.1737 | 0.6508 |
+| No log | 11.0 | 275 | 0.8216 | 0.7292 | 0.1572 | 0.2018 | 0.1764 | 0.6554 |
+| No log | 12.0 | 300 | 0.8044 | 0.7299 | 0.2295 | 0.2081 | 0.1786 | 0.6605 |
+| No log | 13.0 | 325 | 0.8108 | 0.732 | 0.2304 | 0.2091 | 0.1797 | 0.662 |
+| No log | 14.0 | 350 | 0.7920 | 0.7306 | 0.2062 | 0.22 | 0.1877 | 0.6711 |
+| No log | 15.0 | 375 | 0.8025 | 0.7332 | 0.2164 | 0.2153 | 0.1836 | 0.6674 |
+| No log | 16.0 | 400 | 0.7937 | 0.7335 | 0.1982 | 0.2248 | 0.2039 | 0.6813 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.12.0
+- Tokenizers 0.15.0

config.json

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+{
+ "_name_or_path": "google/mobilebert-uncased",
+ "architectures": [
+ "MobileBertForTokenClassification"
+ ],
+ "attention_probs_dropout_prob": 0.1,
+ "classifier_activation": false,
+ "classifier_dropout": null,
+ "embedding_size": 128,
+ "hidden_act": "relu",
+ "hidden_dropout_prob": 0.0,
+ "hidden_size": 512,
+ "id2label": {
+ "0": "null",
+ "1": "GeneOrGeneProduct",
+ "2": "DiseaseOrPhenotypicFeature",
+ "3": "ChemicalEntity",
+ "4": "OrganismTaxon",
+ "5": "SequenceVariant",
+ "6": "CellLine"
+ },
+ "initializer_range": 0.02,
+ "intermediate_size": 512,
+ "intra_bottleneck_size": 128,
+ "key_query_shared_bottleneck": true,
+ "label2id": {
+ "CellLine": 6,
+ "ChemicalEntity": 3,
+ "DiseaseOrPhenotypicFeature": 2,
+ "GeneOrGeneProduct": 1,
+ "OrganismTaxon": 4,
+ "SequenceVariant": 5,
+ "null": 0
+ },
+ "layer_norm_eps": 1e-12,
+ "max_position_embeddings": 512,
+ "model_type": "mobilebert",
+ "normalization_type": "no_norm",
+ "num_attention_heads": 4,
+ "num_feedforward_networks": 4,
+ "num_hidden_layers": 24,
+ "pad_token_id": 0,
+ "torch_dtype": "float32",
+ "transformers_version": "4.35.2",
+ "trigram_input": true,
+ "true_hidden_size": 128,
+ "type_vocab_size": 2,
+ "use_bottleneck": true,
+ "use_bottleneck_attention": false,
+ "vocab_size": 30522
+}

model.safetensors

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+size 98480380

special_tokens_map.json

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+{
+ "cls_token": "[CLS]",
+ "mask_token": "[MASK]",
+ "pad_token": "[PAD]",
+ "sep_token": "[SEP]",
+ "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+ "add_prefix_space": true,
+ "added_tokens_decoder": {
+ "0": {
+ "content": "[PAD]",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
+ },
+ "100": {
+ "content": "[UNK]",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
+ },
+ "101": {
+ "content": "[CLS]",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
+ },
+ "102": {
+ "content": "[SEP]",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
+ },
+ "103": {
+ "content": "[MASK]",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
+ }
+ },
+ "clean_up_tokenization_spaces": true,
+ "cls_token": "[CLS]",
+ "do_lower_case": true,
+ "mask_token": "[MASK]",
+ "model_max_length": 512,
+ "pad_token": "[PAD]",
+ "sep_token": "[SEP]",
+ "strip_accents": null,
+ "tokenize_chinese_chars": true,
+ "tokenizer_class": "MobileBertTokenizer",
+ "unk_token": "[UNK]"
+}

training_args.bin

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+size 4219