End of training

README.md

@@ -3,9 +3,10 @@ library_name: transformers
 license: apache-2.0
 base_model: michiyasunaga/BioLinkBERT-base
 tags:
+- token-classification
 - generated_from_trainer
 datasets:
-- drugtemist-en-fasttext-9-ner
+- Rodrigo1771/drugtemist-en-fasttext-9-ner
 metrics:
 - precision
 - recall
@@ -18,8 +19,8 @@ model-index:
       name: Token Classification
       type: token-classification
     dataset:
-      name: drugtemist-en-fasttext-9-ner
-      type: drugtemist-en-fasttext-9-ner
+      name: Rodrigo1771/drugtemist-en-fasttext-9-ner
+      type: Rodrigo1771/drugtemist-en-fasttext-9-ner
       config: DrugTEMIST English NER
       split: validation
       args: DrugTEMIST English NER
@@ -43,7 +44,7 @@ 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-fasttext-9-ner dataset.
+This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-base](https://huggingface.co/michiyasunaga/BioLinkBERT-base) on the Rodrigo1771/drugtemist-en-fasttext-9-ner dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.0071
 - Precision: 0.9312

all_results.json

@@ -0,0 +1,26 @@
+{
+    "epoch": 9.988518943742825,
+    "eval_accuracy": 0.998772081600759,
+    "eval_f1": 0.9320297951582869,
+    "eval_loss": 0.007080046460032463,
+    "eval_precision": 0.9311627906976744,
+    "eval_recall": 0.9328984156570364,
+    "eval_runtime": 15.1487,
+    "eval_samples": 6946,
+    "eval_samples_per_second": 458.52,
+    "eval_steps_per_second": 57.365,
+    "predict_accuracy": 0.9986133871171058,
+    "predict_f1": 0.9153020892151327,
+    "predict_loss": 0.00810017716139555,
+    "predict_precision": 0.8906593406593407,
+    "predict_recall": 0.9413472706155633,
+    "predict_runtime": 28.412,
+    "predict_samples_per_second": 517.915,
+    "predict_steps_per_second": 64.761,
+    "total_flos": 1.1084127968547612e+16,
+    "train_loss": 0.003044272955806776,
+    "train_runtime": 1809.5975,
+    "train_samples": 27841,
+    "train_samples_per_second": 153.852,
+    "train_steps_per_second": 2.404
+}

eval_results.json

@@ -0,0 +1,12 @@
+{
+    "epoch": 9.988518943742825,
+    "eval_accuracy": 0.998772081600759,
+    "eval_f1": 0.9320297951582869,
+    "eval_loss": 0.007080046460032463,
+    "eval_precision": 0.9311627906976744,
+    "eval_recall": 0.9328984156570364,
+    "eval_runtime": 15.1487,
+    "eval_samples": 6946,
+    "eval_samples_per_second": 458.52,
+    "eval_steps_per_second": 57.365
+}

predict_results.json

@@ -0,0 +1,10 @@
+{
+    "predict_accuracy": 0.9986133871171058,
+    "predict_f1": 0.9153020892151327,
+    "predict_loss": 0.00810017716139555,
+    "predict_precision": 0.8906593406593407,
+    "predict_recall": 0.9413472706155633,
+    "predict_runtime": 28.412,
+    "predict_samples_per_second": 517.915,
+    "predict_steps_per_second": 64.761
+}

tb/events.out.tfevents.1725909805.3d77e24b7860.2139.1

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3e35af360d87d0f987e4188a8e1ebe9527ad33825e2c4b1bb1e23c5899011a7d
+size 560

train.log

@@ -1426,3 +1426,51 @@ Training completed. Do not forget to share your model on huggingface.co/models =
 {'eval_loss': 0.007080046460032463, 'eval_precision': 0.9311627906976744, 'eval_recall': 0.9328984156570364, 'eval_f1': 0.9320297951582869, 'eval_accuracy': 0.998772081600759, 'eval_runtime': 15.2679, 'eval_samples_per_second': 454.941, 'eval_steps_per_second': 56.917, 'epoch': 9.99}
 {'train_runtime': 1809.5975, 'train_samples_per_second': 153.852, 'train_steps_per_second': 2.404, 'train_loss': 0.003044272955806776, 'epoch': 9.99}
 
+***** train metrics *****
+  epoch                    =     9.9885
+  total_flos               = 10322898GF
+  train_loss               =      0.003
+  train_runtime            = 0:30:09.59
+  train_samples            =      27841
+  train_samples_per_second =    153.852
+  train_steps_per_second   =      2.404
+09/09/2024 19:23:10 - INFO - __main__ -   *** Evaluate ***
+[INFO|trainer.py:811] 2024-09-09 19:23:10,626 >> The following columns in the evaluation set don't have a corresponding argument in `BertForTokenClassification.forward` and have been ignored: tokens, ner_tags, id. If tokens, ner_tags, id are not expected by `BertForTokenClassification.forward`,  you can safely ignore this message.
+[INFO|trainer.py:3819] 2024-09-09 19:23:10,629 >> 
+***** Running Evaluation *****
+[INFO|trainer.py:3821] 2024-09-09 19:23:10,629 >>   Num examples = 6946
+[INFO|trainer.py:3824] 2024-09-09 19:23:10,629 >>   Batch size = 8
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+***** eval metrics *****
+  epoch                   =     9.9885
+  eval_accuracy           =     0.9988
+  eval_f1                 =      0.932
+  eval_loss               =     0.0071
+  eval_precision          =     0.9312
+  eval_recall             =     0.9329
+  eval_runtime            = 0:00:15.14
+  eval_samples            =       6946
+  eval_samples_per_second =     458.52
+  eval_steps_per_second   =     57.365
+09/09/2024 19:23:25 - INFO - __main__ -   *** Predict ***
+[INFO|trainer.py:811] 2024-09-09 19:23:25,784 >> The following columns in the test set don't have a corresponding argument in `BertForTokenClassification.forward` and have been ignored: tokens, ner_tags, id. If tokens, ner_tags, id are not expected by `BertForTokenClassification.forward`,  you can safely ignore this message.
+[INFO|trainer.py:3819] 2024-09-09 19:23:25,786 >> 
+***** Running Prediction *****
+[INFO|trainer.py:3821] 2024-09-09 19:23:25,786 >>   Num examples = 14715
+[INFO|trainer.py:3824] 2024-09-09 19:23:25,786 >>   Batch size = 8
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+[INFO|trainer.py:3503] 2024-09-09 19:23:54,954 >> Saving model checkpoint to /content/dissertation/scripts/ner/output
+[INFO|configuration_utils.py:472] 2024-09-09 19:23:54,956 >> Configuration saved in /content/dissertation/scripts/ner/output/config.json
+[INFO|modeling_utils.py:2799] 2024-09-09 19:23:56,214 >> Model weights saved in /content/dissertation/scripts/ner/output/model.safetensors
+[INFO|tokenization_utils_base.py:2684] 2024-09-09 19:23:56,215 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2693] 2024-09-09 19:23:56,216 >> Special tokens file saved in /content/dissertation/scripts/ner/output/special_tokens_map.json
+***** predict metrics *****
+  predict_accuracy           =     0.9986
+  predict_f1                 =     0.9153
+  predict_loss               =     0.0081
+  predict_precision          =     0.8907
+  predict_recall             =     0.9413
+  predict_runtime            = 0:00:28.41
+  predict_samples_per_second =    517.915
+  predict_steps_per_second   =     64.761
+

train_results.json

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+}

trainer_state.json

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