Model save

README.md

@@ -1,3 +1,77 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+base_model: google/flan-t5-large
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+- f1
+- recall
+- precision
+model-index:
+- name: KGQA-1
+  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. -->
+
+# KGQA-1
+
+This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.0784
+- Rouge1: 72.8963
+- Rouge2: 60.8929
+- Rougel: 69.6657
+- Rougelsum: 72.9329
+- Gen Len: 4.8819
+- F1: 0.7593
+- Recall: 0.7681
+- Precision: 0.7508
+
+## 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: 0.001
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine_with_restarts
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len | F1     | Recall | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:------:|:------:|:---------:|
+| 2.8587        | 1.0   | 598  | 2.2931          | 49.5203 | 26.8249 | 43.3252 | 49.5005   | 4.6943  | 0.5633 | 0.5546 | 0.5723    |
+| 1.7685        | 2.0   | 1196 | 1.6857          | 52.6345 | 31.7615 | 46.5617 | 52.5831   | 4.7965  | 0.619  | 0.6295 | 0.6088    |
+| 0.8979        | 3.0   | 1794 | 1.3095          | 65.3839 | 49.1969 | 60.9907 | 65.2835   | 4.8928  | 0.6898 | 0.6806 | 0.6992    |
+| 0.4881        | 4.0   | 2392 | 1.4524          | 68.0576 | 53.7819 | 64.3964 | 67.9986   | 4.835   | 0.7239 | 0.7106 | 0.7378    |
+| 1.2094        | 5.0   | 2990 | 3.2070          | 18.934  | 4.1916  | 14.7003 | 18.9198   | 6.0159  | 0.0005 | 0.001  | 0.0003    |
+| 0.7018        | 6.0   | 3588 | 1.3772          | 68.1255 | 54.2242 | 64.3339 | 68.1513   | 4.7588  | 0.7125 | 0.69   | 0.7366    |
+| 0.3275        | 7.0   | 4186 | 1.5585          | 72.2516 | 60.2665 | 68.9117 | 72.2482   | 4.9246  | 0.7643 | 0.7827 | 0.7468    |
+| 0.112         | 8.0   | 4784 | 2.0784          | 72.8963 | 60.8929 | 69.6657 | 72.9329   | 4.8819  | 0.7593 | 0.7681 | 0.7508    |
+
+
+### Framework versions
+
+- Transformers 4.43.3
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

generation_config.json

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+{
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.43.3"
+}

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