Training in progress, step 200

README.md

@@ -48,9 +48,6 @@ The following hyperparameters were used during training:
 - eval_batch_size: 8
 - seed: 42
 - distributed_type: multi-GPU
-- num_devices: 2
-- total_train_batch_size: 16
-- total_eval_batch_size: 16
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - training_steps: 2500
@@ -60,10 +57,10 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Validation Loss | Answer                                                    | Header                                                    | Question                                                  | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 0.0519        | 200.0  | 200  | 0.0001          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2} | 1.0               | 1.0            | 1.0        | 1.0              |
+| 0.07          | 200.0  | 200  | 0.0001          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2} | 1.0               | 1.0            | 1.0        | 1.0              |
 | 0.0001        | 400.0  | 400  | 0.0000          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2} | 1.0               | 1.0            | 1.0        | 1.0              |
 | 0.0001        | 600.0  | 600  | 0.0000          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2} | 1.0               | 1.0            | 1.0        | 1.0              |
-| 0.0           | 800.0  | 800  | 0.0000          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2} | 1.0               | 1.0            | 1.0        | 1.0              |
+| 0.0001        | 800.0  | 800  | 0.0000          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2} | 1.0               | 1.0            | 1.0        | 1.0              |
 | 0.0           | 1000.0 | 1000 | 0.0000          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2} | 1.0               | 1.0            | 1.0        | 1.0              |
 | 0.0           | 1200.0 | 1200 | 0.0000          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2} | 1.0               | 1.0            | 1.0        | 1.0              |
 | 0.0           | 1400.0 | 1400 | 0.0000          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 3} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 1} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 2} | 1.0               | 1.0            | 1.0        | 1.0              |

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