End of training

README.md

@@ -1,6 +1,6 @@
 ---
 license: apache-2.0
-base_model: luluw/t5-base-finetuned-billsum
+base_model: google-t5/t5-base
 tags:
 - generated_from_trainer
 metrics:
@@ -15,14 +15,14 @@ should probably proofread and complete it, then remove this comment. -->
 
 # t5-base-finetuned-billsum
 
-This model is a fine-tuned version of [luluw/t5-base-finetuned-billsum](https://huggingface.co/luluw/t5-base-finetuned-billsum) on an unknown dataset.
+This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.5204
-- Rouge1: 48.9735
-- Rouge2: 29.0909
-- Rougel: 39.1634
-- Rougelsum: 42.7953
-- Gen Len: 112.7247
+- Loss: 1.1725
+- Rouge1: 54.1481
+- Rouge2: 33.3953
+- Rougel: 42.8337
+- Rougelsum: 47.5287
+- Gen Len: 116.8581
 
 ## Model description
 
@@ -42,22 +42,30 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 8
-- eval_batch_size: 8
+- 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
-- lr_scheduler_warmup_steps: 1000
-- num_epochs: 3
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 5
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
 |:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
-| 1.3003        | 0.8442 | 2000 | 1.1182          | 56.5942 | 37.4635 | 45.9359 | 50.3437   | 109.3659 |
-| 1.2443        | 1.6885 | 4000 | 1.1433          | 56.3579 | 36.706  | 45.4519 | 49.8982   | 118.3600 |
-| 1.5978        | 2.5327 | 6000 | 1.5204          | 48.9735 | 29.0909 | 39.1634 | 42.7953   | 112.7247 |
+| 2.5944        | 0.4219 | 500  | 1.2582          | 50.6899 | 31.6418 | 40.2325 | 44.2687   | 111.7541 |
+| 1.3588        | 0.8439 | 1000 | 1.1591          | 55.865  | 35.992  | 44.7636 | 49.2805   | 114.3552 |
+| 1.275         | 1.2658 | 1500 | 1.1214          | 56.3449 | 37.0781 | 45.604  | 49.9711   | 110.7724 |
+| 1.3266        | 1.6878 | 2000 | 1.1791          | 54.4797 | 33.8689 | 43.1813 | 47.8507   | 114.8278 |
+| 1.3591        | 2.1097 | 2500 | 1.1725          | 54.243  | 33.5179 | 42.9187 | 47.6231   | 116.4601 |
+| 1.3484        | 2.5316 | 3000 | 1.1724          | 54.1433 | 33.3914 | 42.8348 | 47.5267   | 116.7736 |
+| 1.3467        | 2.9536 | 3500 | 1.1724          | 54.1359 | 33.3794 | 42.8167 | 47.5153   | 116.7819 |
+| 1.3483        | 3.3755 | 4000 | 1.1724          | 54.1446 | 33.3947 | 42.8274 | 47.5313   | 116.8529 |
+| 1.342         | 3.7975 | 4500 | 1.1724          | 54.1341 | 33.3888 | 42.8239 | 47.5291   | 116.7957 |
+| 1.3475        | 4.2194 | 5000 | 1.1725          | 54.1411 | 33.3931 | 42.8224 | 47.5218   | 116.8229 |
+| 1.3542        | 4.6414 | 5500 | 1.1725          | 54.1481 | 33.3953 | 42.8337 | 47.5287   | 116.8581 |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:79d88be4a2f9320b4fed7073b05ca0dd27ee53505c34170066ec66e92894b344
+oid sha256:82a1bbbe67948726b2cbeb41a61f6fe96cf96edc2d9b61b3806425534e3ac46c
 size 891644712