End of training

README.md

@@ -1,64 +1,64 @@
----
-license: apache-2.0
-base_model: bert-base-cased
-tags:
-- generated_from_trainer
-metrics:
-- accuracy
-- f1
-model-index:
-- name: finetuned-bert-mrpc
-  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. -->
-
-# finetuned-bert-mrpc
-
-This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.4707
-- Accuracy: 0.8505
-- F1: 0.8961
-
-## 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: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 16
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 3.0
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.5734        | 1.0   | 230  | 0.4219          | 0.8260   | 0.8757 |
-| 0.3508        | 2.0   | 460  | 0.3693          | 0.8382   | 0.8870 |
-| 0.1863        | 3.0   | 690  | 0.4707          | 0.8505   | 0.8961 |
-
-
-### Framework versions
-
-- Transformers 4.40.2
-- Pytorch 2.1.2
-- Datasets 2.19.1
-- Tokenizers 0.19.1
+---
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: finetuned-bert-mrpc
+  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. -->
+
+# finetuned-bert-mrpc
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5326
+- Accuracy: 0.8529
+- F1: 0.8997
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.5726        | 1.0   | 230  | 0.4435          | 0.8039   | 0.8667 |
+| 0.3639        | 2.0   | 460  | 0.4053          | 0.8456   | 0.8919 |
+| 0.2098        | 3.0   | 690  | 0.5326          | 0.8529   | 0.8997 |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.1.1
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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