End of training

README.md

@@ -4,6 +4,9 @@ license: mit
 base_model: VietAI/vit5-base
 tags:
 - generated_from_trainer
+metrics:
+- precision
+- recall
 model-index:
 - name: ViNormT5
   results: []
@@ -16,9 +19,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2178
-- Bleu Score: 78.7261
-- Gen Len: 12.7826
+- Loss: 0.2401
+- Bleu Score: 78.0055
+- Precision: 51.2545
+- Recall: 51.2545
+- Gen Len: 12.7897
+- Err: 51.2545
 
 ## Model description
 
@@ -38,20 +44,18 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0001
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 4
+- eval_batch_size: 4
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 1
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Bleu Score | Gen Len |
-|:-------------:|:-----:|:----:|:---------------:|:----------:|:-------:|
-| 0.4635        | 1.0   | 419  | 0.2255          | 77.2678    | 12.7969 |
-| 0.166         | 2.0   | 838  | 0.2026          | 78.2851    | 12.8041 |
-| 0.0752        | 3.0   | 1257 | 0.2178          | 78.7261    | 12.7826 |
+| Training Loss | Epoch | Step | Validation Loss | Bleu Score | Precision | Recall  | Gen Len | Err     |
+|:-------------:|:-----:|:----:|:---------------:|:----------:|:---------:|:-------:|:-------:|:-------:|
+| 0.4488        | 1.0   | 1675 | 0.2401          | 78.0055    | 51.2545   | 51.2545 | 12.7897 | 51.2545 |
 
 
 ### Framework versions

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