Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: t5-small
+tags:
+- generated_from_trainer
+datasets:
+- wikisql
+model-index:
+- name: t5-small-finetuned-wikisql
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# t5-small-finetuned-wikisql
+
+This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wikisql dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1247
+- Model Preparation Time: 0.0028
+- Rouge1 Precision: 0.873
+- Rouge1 Recall: 0.873
+- Rouge1 Fmeasure: 0.873
+- Rouge2 Precision: 0.7718
+- Rouge2 Recall: 0.7718
+- Rouge2 Fmeasure: 0.7718
+- Rougel Precision: 0.8599
+- Rougel Recall: 0.8599
+- Rougel Fmeasure: 0.8599
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Model Preparation Time | Rouge1 Precision | Rouge1 Recall | Rouge1 Fmeasure | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | Rougel Precision | Rougel Recall | Rougel Fmeasure |
+|:-------------:|:-----:|:-----:|:---------------:|:----------------------:|:----------------:|:-------------:|:---------------:|:----------------:|:-------------:|:---------------:|:----------------:|:-------------:|:---------------:|
+| 0.1942        | 1.0   | 4049  | 0.1561          | 0.0028                 | 0.863            | 0.863         | 0.863           | 0.7471           | 0.7471        | 0.7471          | 0.847            | 0.847         | 0.847           |
+| 0.1646        | 2.0   | 8098  | 0.1373          | 0.0028                 | 0.8698           | 0.8698        | 0.8698          | 0.763            | 0.763         | 0.763           | 0.8554           | 0.8554        | 0.8554          |
+| 0.147         | 3.0   | 12147 | 0.1297          | 0.0028                 | 0.8723           | 0.8723        | 0.8723          | 0.7684           | 0.7684        | 0.7684          | 0.8587           | 0.8587        | 0.8587          |
+| 0.1412        | 4.0   | 16196 | 0.1256          | 0.0028                 | 0.8725           | 0.8725        | 0.8725          | 0.7712           | 0.7712        | 0.7712          | 0.8594           | 0.8594        | 0.8594          |
+| 0.14          | 5.0   | 20245 | 0.1247          | 0.0028                 | 0.873            | 0.873         | 0.873           | 0.7718           | 0.7718        | 0.7718          | 0.8599           | 0.8599        | 0.8599          |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

generation_config.json

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+{
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.47.1"
+}