Training complete

README.md

@@ -1,72 +1,74 @@
----
-license: apache-2.0
-base_model: pabRomero/BERT-full-finetuned-ner-pablo
-tags:
-- generated_from_trainer
-metrics:
-- precision
-- recall
-- f1
-- accuracy
-model-index:
-- name: BERT-full-finetuned-ner-pablo
-  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. -->
-
-# BERT-full-finetuned-ner-pablo
-
-This model is a fine-tuned version of [pabRomero/BERT-full-finetuned-ner-pablo](https://huggingface.co/pabRomero/BERT-full-finetuned-ner-pablo) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.1343
-- Precision: 0.7987
-- Recall: 0.7855
-- F1: 0.7920
-- Accuracy: 0.9688
-
-## 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: 0.0002
-- train_batch_size: 4
-- eval_batch_size: 4
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 16
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.05
-- num_epochs: 3
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.1038        | 0.9998 | 2608 | 0.1377          | 0.7579    | 0.7370 | 0.7473 | 0.9645   |
-| 0.0715        | 2.0    | 5217 | 0.1353          | 0.7700    | 0.7625 | 0.7663 | 0.9667   |
-| 0.0477        | 2.9994 | 7824 | 0.1343          | 0.7987    | 0.7855 | 0.7920 | 0.9688   |
-
-
-### Framework versions
-
-- Transformers 4.44.0
-- Pytorch 2.4.0+cu124
-- Datasets 2.21.0
-- Tokenizers 0.19.1
+---
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: BERT-full-finetuned-ner-pablo
+  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. -->
+
+# BERT-full-finetuned-ner-pablo
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1071
+- Precision: 0.7993
+- Recall: 0.7887
+- F1: 0.7940
+- Accuracy: 0.9768
+
+## 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: 0.0002
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.05
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 0.9923 | 97   | 0.1037          | 0.7655    | 0.7399 | 0.7525 | 0.9725   |
+| No log        | 1.9949 | 195  | 0.0907          | 0.8123    | 0.7488 | 0.7792 | 0.9759   |
+| No log        | 2.9974 | 293  | 0.0922          | 0.7739    | 0.7872 | 0.7805 | 0.9758   |
+| No log        | 4.0    | 391  | 0.0986          | 0.7856    | 0.7895 | 0.7875 | 0.9760   |
+| No log        | 4.9616 | 485  | 0.1071          | 0.7993    | 0.7887 | 0.7940 | 0.9768   |
+
+
+### Framework versions
+
+- Transformers 4.44.0
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

runs/Aug20_15-46-03_669c7f3efb42/events.out.tfevents.1724168764.669c7f3efb42.2417.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:08b9cde2efe86a6859ebcdd96887124c6ddd41a3b63c98d61945d874f8b5a4a5
-size 7623
+oid sha256:0ce55810aeb4a970510a12ec1056bcb958b399e74ca31e59f6794deb4aca1726
+size 8449