cgallegoan
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t5-small-finetuned-acbsql

Text2Text Generation

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text-generation-inference

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cgallegoan commited on May 30, 2023

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update model card README.md

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@@ -14,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
 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: 0.2372
-- Rouge2 Precision: 0.4316
-- Rouge2 Recall: 0.1587
-- Rouge2 Fmeasure: 0.2284
 ## Model description
@@ -42,17 +42,22 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 5
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
 |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
-| No log        | 1.0   | 80   | 0.8580          | 0.0363           | 0.0134        | 0.0184          |
-| No log        | 2.0   | 160  | 0.3950          | 0.3302           | 0.1213        | 0.1741          |
-| No log        | 3.0   | 240  | 0.2827          | 0.4003           | 0.1499        | 0.2143          |
-| No log        | 4.0   | 320  | 0.2479          | 0.4308           | 0.1593        | 0.229           |
-| No log        | 5.0   | 400  | 0.2372          | 0.4316           | 0.1587        | 0.2284          |
 ### Framework versions

 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: 0.1089
+- Rouge2 Precision: 0.5759
+- Rouge2 Recall: 0.2135
+- Rouge2 Fmeasure: 0.306
 ## Model description
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
+- num_epochs: 10
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
 |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
+| No log        | 1.0   | 79   | 0.3504          | 0.3762           | 0.1435        | 0.2038          |
+| No log        | 2.0   | 158  | 0.2444          | 0.4303           | 0.1587        | 0.2278          |
+| No log        | 3.0   | 237  | 0.1943          | 0.4982           | 0.1802        | 0.2612          |
+| No log        | 4.0   | 316  | 0.1622          | 0.5267           | 0.1882        | 0.2741          |
+| No log        | 5.0   | 395  | 0.1423          | 0.5596           | 0.2042        | 0.2946          |
+| No log        | 6.0   | 474  | 0.1284          | 0.5718           | 0.2118        | 0.3038          |
+| 0.365         | 7.0   | 553  | 0.1199          | 0.574            | 0.2119        | 0.3042          |
+| 0.365         | 8.0   | 632  | 0.1139          | 0.5761           | 0.2135        | 0.3059          |
+| 0.365         | 9.0   | 711  | 0.1100          | 0.5757           | 0.2134        | 0.3057          |
+| 0.365         | 10.0  | 790  | 0.1089          | 0.5759           | 0.2135        | 0.306           |
 ### Framework versions