Yonadav
/

en_to_kjven_translator

@@ -14,11 +14,11 @@ should probably proofread and complete it, then remove this comment. -->
 # en_to_kjven_translator
-This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9847
-- Bleu: 20.6579
-- Gen Len: 18.0017
 ## Model description
@@ -38,53 +38,39 @@ More information needed
 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: 30
 - mixed_precision_training: Native AMP
 ### Training results
-| Training Loss | Epoch | Step   | Validation Loss | Bleu    | Gen Len |
-|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|
-| 1.5437        | 1.0   | 6105   | 1.3910          | 17.168  | 17.9611 |
-| 1.4232        | 2.0   | 12210  | 1.2885          | 18.0224 | 17.9691 |
-| 1.3474        | 3.0   | 18315  | 1.2305          | 18.5705 | 17.9751 |
-| 1.32          | 4.0   | 24420  | 1.1890          | 18.942  | 17.981  |
-| 1.2733        | 5.0   | 30525  | 1.1597          | 19.2091 | 17.976  |
-| 1.2347        | 6.0   | 36630  | 1.1324          | 19.4233 | 17.9852 |
-| 1.2168        | 7.0   | 42735  | 1.1134          | 19.5744 | 17.9872 |
-| 1.1951        | 8.0   | 48840  | 1.0967          | 19.7628 | 17.9841 |
-| 1.1694        | 9.0   | 54945  | 1.0813          | 19.8682 | 17.9898 |
-| 1.1539        | 10.0  | 61050  | 1.0681          | 20.0338 | 17.989  |
-| 1.1447        | 11.0  | 67155  | 1.0566          | 20.1025 | 17.9912 |
-| 1.1164        | 12.0  | 73260  | 1.0477          | 20.2067 | 17.9904 |
-| 1.1157        | 13.0  | 79365  | 1.0390          | 20.251  | 17.9946 |
-| 1.1145        | 14.0  | 85470  | 1.0310          | 20.3136 | 17.9952 |
-| 1.0927        | 15.0  | 91575  | 1.0252          | 20.3417 | 17.9934 |
-| 1.0837        | 16.0  | 97680  | 1.0185          | 20.407  | 17.9909 |
-| 1.0776        | 17.0  | 103785 | 1.0136          | 20.4439 | 17.9955 |
-| 1.0753        | 18.0  | 109890 | 1.0084          | 20.4762 | 17.9956 |
-| 1.0569        | 19.0  | 115995 | 1.0039          | 20.4643 | 17.9995 |
-| 1.0676        | 20.0  | 122100 | 1.0001          | 20.5041 | 18.002  |
-| 1.0593        | 21.0  | 128205 | 0.9977          | 20.5265 | 18.0009 |
-| 1.0555        | 22.0  | 134310 | 0.9952          | 20.5503 | 18.0018 |
-| 1.0302        | 23.0  | 140415 | 0.9927          | 20.5968 | 18.0005 |
-| 1.045         | 24.0  | 146520 | 0.9906          | 20.6097 | 18.0012 |
-| 1.0407        | 25.0  | 152625 | 0.9889          | 20.6209 | 18.0015 |
-| 1.0282        | 26.0  | 158730 | 0.9867          | 20.6371 | 18.0018 |
-| 1.024         | 27.0  | 164835 | 0.9862          | 20.6404 | 18.0022 |
-| 1.0411        | 28.0  | 170940 | 0.9851          | 20.6558 | 18.0018 |
-| 1.0292        | 29.0  | 177045 | 0.9848          | 20.6559 | 18.0016 |
-| 1.0149        | 30.0  | 183150 | 0.9847          | 20.6579 | 18.0017 |
 ### Framework versions
-- Transformers 4.27.4
 - Pytorch 2.0.0+cu118
 - Datasets 2.11.0
 - Tokenizers 0.13.3

 # en_to_kjven_translator
+This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.7384
+- Bleu: 24.3137
+- Gen Len: 18.018
 ## Model description
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
+- num_epochs: 16
 - mixed_precision_training: Native AMP
 ### Training results
+| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
+| 1.0945        | 1.0   | 2993  | 0.9622          | 21.6701 | 17.9817 |
+| 0.9915        | 2.0   | 5986  | 0.8925          | 22.5111 | 17.9861 |
+| 0.9306        | 3.0   | 8979  | 0.8543          | 22.9079 | 18.0025 |
+| 0.889         | 4.0   | 11972 | 0.8257          | 23.2629 | 17.9987 |
+| 0.8616        | 5.0   | 14965 | 0.8053          | 23.4706 | 18.0027 |
+| 0.8412        | 6.0   | 17958 | 0.7886          | 23.6554 | 18.0092 |
+| 0.811         | 7.0   | 20951 | 0.7769          | 23.8119 | 18.0106 |
+| 0.8024        | 8.0   | 23944 | 0.7675          | 23.9582 | 18.0114 |
+| 0.7898        | 9.0   | 26937 | 0.7583          | 24.0002 | 18.012  |
+| 0.7802        | 10.0  | 29930 | 0.7538          | 24.0943 | 18.0156 |
+| 0.7645        | 11.0  | 32923 | 0.7491          | 24.1756 | 18.0168 |
+| 0.7565        | 12.0  | 35916 | 0.7445          | 24.2229 | 18.0158 |
+| 0.7553        | 13.0  | 38909 | 0.7410          | 24.2709 | 18.0159 |
+| 0.7454        | 14.0  | 41902 | 0.7399          | 24.2593 | 18.0205 |
+| 0.7424        | 15.0  | 44895 | 0.7388          | 24.3007 | 18.0174 |
+| 0.7461        | 16.0  | 47888 | 0.7384          | 24.3137 | 18.018  |
 ### Framework versions
+- Transformers 4.28.1
 - Pytorch 2.0.0+cu118
 - Datasets 2.11.0
 - Tokenizers 0.13.3