diff --git "a/train.log" "b/train.log"
--- "a/train.log"
+++ "b/train.log"
@@ -1489,4 +1489,144 @@ Passing `trust_remote_code=True` will be mandatory to load this metric from the
 [INFO|tokenization_utils_base.py:2497] 2024-05-13 12:25:47,405 >> Special tokens file saved in /content/dissertation/scripts/ner/output/checkpoint-15313/special_tokens_map.json
 [INFO|tokenization_utils_base.py:2488] 2024-05-13 12:25:52,250 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/tokenizer_config.json
 [INFO|tokenization_utils_base.py:2497] 2024-05-13 12:25:52,250 >> Special tokens file saved in /content/dissertation/scripts/ner/output/special_tokens_map.json
-
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100%|██████████| 17010/17010 [54:48<00:00,  5.59it/s][INFO|trainer.py:786] 2024-05-13 12:31:00,788 >> The following columns in the evaluation set don't have a corresponding argument in `RobertaForTokenClassification.forward` and have been ignored: tokens, ner_tags, id. If tokens, ner_tags, id are not expected by `RobertaForTokenClassification.forward`,  you can safely ignore this message.
+[INFO|trainer.py:3614] 2024-05-13 12:31:00,790 >> ***** Running Evaluation *****
+[INFO|trainer.py:3616] 2024-05-13 12:31:00,790 >>   Num examples = 6807
+[INFO|trainer.py:3619] 2024-05-13 12:31:00,790 >>   Batch size = 8
+{'eval_loss': 1.102479100227356, 'eval_precision': 0.31328972130119187, 'eval_recall': 0.8179691155825924, 'eval_f1': 0.45305514157973176, 'eval_accuracy': 0.8523937357107058, 'eval_runtime': 16.1914, 'eval_samples_per_second': 420.409, 'eval_steps_per_second': 52.559, 'epoch': 9.0}
+{'loss': 0.0171, 'grad_norm': 3.3734261989593506, 'learning_rate': 4.438565549676661e-06, 'epoch': 9.11}
+{'loss': 0.013, 'grad_norm': 0.19828377664089203, 'learning_rate': 2.9688418577307467e-06, 'epoch': 9.4}
+{'loss': 0.0133, 'grad_norm': 1.491190791130066, 'learning_rate': 1.4991181657848325e-06, 'epoch': 9.7}
+{'loss': 0.0135, 'grad_norm': 2.5641109943389893, 'learning_rate': 2.9394473838918286e-08, 'epoch': 9.99}
+
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+  _warn_prf(average, modifier, msg_start, len(result))
+
                                                     
+
                                                 

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                                                 [INFO|trainer.py:3305] 2024-05-13 12:31:17,114 >> Saving model checkpoint to /content/dissertation/scripts/ner/output/checkpoint-17010
+[INFO|configuration_utils.py:471] 2024-05-13 12:31:17,115 >> Configuration saved in /content/dissertation/scripts/ner/output/checkpoint-17010/config.json
+[INFO|modeling_utils.py:2590] 2024-05-13 12:31:18,096 >> Model weights saved in /content/dissertation/scripts/ner/output/checkpoint-17010/model.safetensors
+[INFO|tokenization_utils_base.py:2488] 2024-05-13 12:31:18,097 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/checkpoint-17010/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2497] 2024-05-13 12:31:18,097 >> Special tokens file saved in /content/dissertation/scripts/ner/output/checkpoint-17010/special_tokens_map.json
+[INFO|tokenization_utils_base.py:2488] 2024-05-13 12:31:23,153 >> tokenizer config file saved in /content/dissertation/scripts/ner/output/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2497] 2024-05-13 12:31:23,153 >> Special tokens file saved in /content/dissertation/scripts/ner/output/special_tokens_map.json
+[INFO|trainer.py:2316] 2024-05-13 12:31:23,201 >> 
+
+Training completed. Do not forget to share your model on huggingface.co/models =)
+
+
+[INFO|trainer.py:2521] 2024-05-13 12:31:23,201 >> Loading best model from /content/dissertation/scripts/ner/output/checkpoint-11910 (score: 0.46305870034683594).
+
                                                     

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+[INFO|trainer.py:4035] 2024-05-13 12:31:23,414 >> Waiting for the current checkpoint push to be finished, this might take a couple of minutes.