Training complete

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- summarization
+- generated_from_trainer
+datasets:
+- gov_report_summarization_dataset
+metrics:
+- rouge
+base_model: google/flan-t5-base
+model-index:
+- name: flan-t5-base-finetuned-govReport-3072
+  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. -->
+
+# flan-t5-base-finetuned-govReport-3072
+
+This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the gov_report_summarization_dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: nan
+- Rouge1: 0.042
+- Rouge2: 0.0216
+- Rougel: 0.0379
+- Rougelsum: 0.0406
+
+## 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: 3e-05
+- 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: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
+| 0.0           | 1.0   | 250  | nan             | 0.042  | 0.0216 | 0.0379 | 0.0406    |
+| 0.0           | 2.0   | 500  | nan             | 0.042  | 0.0216 | 0.0379 | 0.0406    |
+| 0.0           | 3.0   | 750  | nan             | 0.042  | 0.0216 | 0.0379 | 0.0406    |
+| 0.0           | 4.0   | 1000 | nan             | 0.042  | 0.0216 | 0.0379 | 0.0406    |
+| 0.0           | 5.0   | 1250 | nan             | 0.042  | 0.0216 | 0.0379 | 0.0406    |
+| 0.0           | 6.0   | 1500 | nan             | 0.042  | 0.0216 | 0.0379 | 0.0406    |
+| 0.0           | 7.0   | 1750 | nan             | 0.042  | 0.0216 | 0.0379 | 0.0406    |
+| 0.0           | 8.0   | 2000 | nan             | 0.042  | 0.0216 | 0.0379 | 0.0406    |
+| 0.0           | 9.0   | 2250 | nan             | 0.042  | 0.0216 | 0.0379 | 0.0406    |
+| 0.0           | 10.0  | 2500 | nan             | 0.042  | 0.0216 | 0.0379 | 0.0406    |
+
+
+### Framework versions
+
+- PEFT 0.8.2
+- Transformers 4.37.0
+- Pytorch 2.1.2
+- Datasets 2.1.0
+- Tokenizers 0.15.1