Model save

README.md

@@ -0,0 +1,102 @@
+---
+library_name: transformers
+license: apache-2.0
+base_model: michiyasunaga/BioLinkBERT-base
+tags:
+- generated_from_trainer
+datasets:
+- drugtemist-en-9-ner
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: output
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: drugtemist-en-9-ner
+      type: drugtemist-en-9-ner
+      config: DrugTEMIST English NER
+      split: validation
+      args: DrugTEMIST English NER
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.924860853432282
+    - name: Recall
+      type: recall
+      value: 0.9291705498602051
+    - name: F1
+      type: f1
+      value: 0.9270106927010694
+    - name: Accuracy
+      type: accuracy
+      value: 0.9986534758462869
+---
+
+<!-- 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. -->
+
+# output
+
+This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-base](https://huggingface.co/michiyasunaga/BioLinkBERT-base) on the drugtemist-en-9-ner dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0071
+- Precision: 0.9249
+- Recall: 0.9292
+- F1: 0.9270
+- Accuracy: 0.9987
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 437  | 0.0047          | 0.8995    | 0.9254 | 0.9123 | 0.9985   |
+| 0.0144        | 2.0   | 874  | 0.0053          | 0.8960    | 0.9310 | 0.9132 | 0.9985   |
+| 0.0038        | 3.0   | 1311 | 0.0046          | 0.9298    | 0.9376 | 0.9336 | 0.9988   |
+| 0.0022        | 4.0   | 1748 | 0.0055          | 0.9202    | 0.9245 | 0.9224 | 0.9986   |
+| 0.0019        | 5.0   | 2185 | 0.0053          | 0.9118    | 0.9348 | 0.9231 | 0.9986   |
+| 0.0014        | 6.0   | 2622 | 0.0054          | 0.9194    | 0.9254 | 0.9224 | 0.9986   |
+| 0.0009        | 7.0   | 3059 | 0.0073          | 0.9324    | 0.9254 | 0.9289 | 0.9986   |
+| 0.0009        | 8.0   | 3496 | 0.0065          | 0.9341    | 0.9254 | 0.9298 | 0.9987   |
+| 0.0005        | 9.0   | 3933 | 0.0069          | 0.9326    | 0.9292 | 0.9309 | 0.9987   |
+| 0.0004        | 10.0  | 4370 | 0.0071          | 0.9249    | 0.9292 | 0.9270 | 0.9987   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

model.safetensors

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tb/events.out.tfevents.1725569221.c3806e32a2f8.1237.0

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train.log

@@ -1267,3 +1267,16 @@ Training completed. Do not forget to share your model on huggingface.co/models =
 [INFO|trainer.py:2632] 2024-09-05 21:04:20,556 >> Loading best model from /content/dissertation/scripts/ner/output/checkpoint-1311 (score: 0.9336426914153132).
 
                                                   
 [INFO|trainer.py:4283] 2024-09-05 21:04:20,741 >> Waiting for the current checkpoint push to be finished, this might take a couple of minutes.
+[INFO|trainer.py:3503] 2024-09-05 21:04:33,780 >> Saving model checkpoint to /content/dissertation/scripts/ner/output
+[INFO|configuration_utils.py:472] 2024-09-05 21:04:33,782 >> Configuration saved in /content/dissertation/scripts/ner/output/config.json
+[INFO|modeling_utils.py:2799] 2024-09-05 21:04:35,047 >> Model weights saved in /content/dissertation/scripts/ner/output/model.safetensors
+[INFO|tokenization_utils_base.py:2684] 2024-09-05 21:04:35,048 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2693] 2024-09-05 21:04:35,049 >> Special tokens file saved in /content/dissertation/scripts/ner/output/special_tokens_map.json
+[INFO|trainer.py:3503] 2024-09-05 21:04:35,062 >> Saving model checkpoint to /content/dissertation/scripts/ner/output
+[INFO|configuration_utils.py:472] 2024-09-05 21:04:35,063 >> Configuration saved in /content/dissertation/scripts/ner/output/config.json
+[INFO|modeling_utils.py:2799] 2024-09-05 21:04:36,304 >> Model weights saved in /content/dissertation/scripts/ner/output/model.safetensors
+[INFO|tokenization_utils_base.py:2684] 2024-09-05 21:04:36,305 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2693] 2024-09-05 21:04:36,305 >> Special tokens file saved in /content/dissertation/scripts/ner/output/special_tokens_map.json
+{'eval_loss': 0.00707679707556963, 'eval_precision': 0.924860853432282, 'eval_recall': 0.9291705498602051, 'eval_f1': 0.9270106927010694, 'eval_accuracy': 0.9986534758462869, 'eval_runtime': 13.4189, 'eval_samples_per_second': 517.629, 'eval_steps_per_second': 64.76, 'epoch': 10.0}
+{'train_runtime': 1039.0289, 'train_samples_per_second': 269.165, 'train_steps_per_second': 4.206, 'train_loss': 0.002938754050150616, 'epoch': 10.0}
+