Change training args

README.md

@@ -3,14 +3,9 @@ license: apache-2.0
 base_model: bert-base-uncased
 tags:
 - generated_from_trainer
-metrics:
-- accuracy
-- f1
 model-index:
 - name: bert-finetuned-mrpc
   results: []
-datasets:
-- glue
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -19,10 +14,6 @@ should probably proofread and complete it, then remove this comment. -->
 # bert-finetuned-mrpc
 
 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.0887
-- Accuracy: 0.8431
-- F1: 0.8904
 
 ## Model description
 
@@ -41,21 +32,16 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 8
-- eval_batch_size: 8
+- learning_rate: 5e-05
+- train_batch_size: 64
+- eval_batch_size: 64
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 5
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| No log        | 1.0   | 459  | 0.8158          | 0.8407   | 0.8900 |
-| 0.0948        | 2.0   | 918  | 1.0599          | 0.8186   | 0.8775 |
-| 0.1667        | 3.0   | 1377 | 1.0887          | 0.8431   | 0.8904 |
 
 
 ### Framework versions
@@ -63,4 +49,4 @@ The following hyperparameters were used during training:
 - Transformers 4.35.2
 - Pytorch 2.1.0+cu121
 - Datasets 2.16.1
-- Tokenizers 0.15.1
+- Tokenizers 0.15.1

model.safetensors

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runs/Jan29_18-08-50_d9917b7fb6ee/events.out.tfevents.1706551735.d9917b7fb6ee.7374.5

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training_args.bin

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