End of training

README.md

@@ -1,8 +1,8 @@
 ---
 license: apache-2.0
+base_model: t5-small
 tags:
 - generated_from_trainer
-base_model: t5-small
 datasets:
 - bills-summarization
 metrics:
@@ -11,31 +11,29 @@ model-index:
 - name: ft-t5-with-dill-sum
   results:
   - task:
-      type: summarization
       name: Summarization
+      type: summarization
     dataset:
       name: billsum
       type: bills-summarization
     metrics:
-    - type: rouge
-      value: 0.1507
-      name: Rouge1
+    - name: Rouge1
+      type: rouge
+      value: 0.0569
 ---
 
 <!-- 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. -->
 
-[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/wit2024/Fine-tuning%20Distilbert%28t5%29/runs/78e1ikhm)
-[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/wit2024/Fine-tuning%20Distilbert%28t5%29/runs/78e1ikhm)
 # ft-t5-with-dill-sum
 
 This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.4943
-- Rouge1: 0.1507
-- Rouge2: 0.0552
-- Rougel: 0.1238
-- Rougelsum: 0.1233
+- Loss: 6.9407
+- Rouge1: 0.0569
+- Rouge2: 0.0174
+- Rougel: 0.05
+- Rougelsum: 0.0501
 - Gen Len: 19.0
 
 ## Model description
@@ -68,16 +66,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
-| No log        | 1.0   | 62   | 2.8341          | 0.135  | 0.0432 | 0.1127 | 0.1123    | 19.0    |
-| No log        | 2.0   | 124  | 2.6121          | 0.1448 | 0.0534 | 0.1213 | 0.1212    | 19.0    |
-| No log        | 3.0   | 186  | 2.5357          | 0.1429 | 0.0493 | 0.1178 | 0.1175    | 19.0    |
-| No log        | 4.0   | 248  | 2.5042          | 0.1477 | 0.0532 | 0.1222 | 0.1218    | 19.0    |
-| No log        | 5.0   | 310  | 2.4943          | 0.1507 | 0.0552 | 0.1238 | 0.1233    | 19.0    |
+| 7.6259        | 1.0   | 62   | 7.2486          | 0.0458 | 0.0123 | 0.0417 | 0.0415    | 19.0    |
+| 7.5212        | 2.0   | 124  | 7.0977          | 0.051  | 0.0143 | 0.0461 | 0.0461    | 19.0    |
+| 7.3879        | 3.0   | 186  | 7.0064          | 0.0567 | 0.0176 | 0.0507 | 0.0507    | 19.0    |
+| 7.2066        | 4.0   | 248  | 6.9585          | 0.0565 | 0.0173 | 0.05   | 0.0501    | 19.0    |
+| 7.1841        | 5.0   | 310  | 6.9407          | 0.0569 | 0.0174 | 0.05   | 0.0501    | 19.0    |
 
 
 ### Framework versions
 
-- Transformers 4.41.0
+- Transformers 4.41.1
 - Pytorch 2.3.0+cu121
 - Datasets 2.19.1
 - Tokenizers 0.19.1

config.json

@@ -55,7 +55,7 @@
     }
   },
   "torch_dtype": "float32",
-  "transformers_version": "4.41.0",
+  "transformers_version": "4.41.1",
   "use_cache": true,
   "vocab_size": 32128
 }

generation_config.json

@@ -2,5 +2,5 @@
   "decoder_start_token_id": 0,
   "eos_token_id": 1,
   "pad_token_id": 0,
-  "transformers_version": "4.41.0"
+  "transformers_version": "4.41.1"
 }

model.safetensors

@@ -1,3 +1,3 @@
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+oid sha256:88f6a6719aa9be96e39aad5384c4cda64d9d4a07fddbf45dfa98a058b1dfa26f
 size 242041896

training_args.bin

@@ -1,3 +1,3 @@
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-size 5304
+oid sha256:b6370480b4fe6f1308bbfdec10e9ff54161b76a807804ef3002ee25da6d587b5
+size 5240