Training in progress, epoch 1

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: michiyasunaga/BioLinkBERT-base
+tags:
+- generated_from_trainer
+datasets:
+- source_data
+metrics:
+- precision
+- recall
+- f1
+model-index:
+- name: SourceData_GeneprodRoles_v1_0_0_BioLinkBERT_base_1.0
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: source_data
+      type: source_data
+      config: ROLES_GP
+      split: validation
+      args: ROLES_GP
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9220255327226995
+    - name: Recall
+      type: recall
+      value: 0.9266873360362509
+    - name: F1
+      type: f1
+      value: 0.9243505566657151
+---
+
+<!-- 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. -->
+
+# SourceData_GeneprodRoles_v1_0_0_BioLinkBERT_base_1.0
+
+This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-base](https://huggingface.co/michiyasunaga/BioLinkBERT-base) on the source_data dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0137
+- Accuracy Score: 0.9948
+- Precision: 0.9220
+- Recall: 0.9267
+- F1: 0.9244
+
+## 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: 0.0001
+- train_batch_size: 64
+- eval_batch_size: 128
+- seed: 42
+- optimizer: Use adafactor and the args are:
+No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 1.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------------:|:---------:|:------:|:------:|
+| 0.0146        | 1.0   | 864  | 0.0137          | 0.9948         | 0.9220    | 0.9267 | 0.9244 |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 1.13.1+cu117
+- Datasets 3.1.0
+- Tokenizers 0.20.3

config.json

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+{
+  "_name_or_path": "michiyasunaga/BioLinkBERT-base",
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": 0.2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "O",
+    "1": "B-CONTROLLED_VAR",
+    "2": "I-CONTROLLED_VAR",
+    "3": "B-MEASURED_VAR",
+    "4": "I-MEASURED_VAR"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-CONTROLLED_VAR": 1,
+    "B-MEASURED_VAR": 3,
+    "I-CONTROLLED_VAR": 2,
+    "I-MEASURED_VAR": 4,
+    "O": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_length": 512,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.46.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 28895
+}

model.safetensors

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+size 430607156

training_args.bin

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