en

README.md

@@ -1,4 +1,6 @@
 ---
+language:
+- en
 license: apache-2.0
 tags:
 - generated_from_trainer
@@ -21,7 +23,7 @@ model-index:
     metrics:
     - name: Rouge1
       type: rouge
-      value: 47.4798
+      value: 47.4485
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,10 +34,10 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the samsum dataset.
 It achieves the following results on the evaluation set:
 - Loss: 1.3772
-- Rouge1: 47.4798
-- Rouge2: 23.9756
-- Rougel: 40.0392
-- Rougelsum: 43.6545
+- Rouge1: 47.4485
+- Rouge2: 23.938
+- Rougel: 40.0491
+- Rougelsum: 43.6954
 - Gen Len: 17.3162
 
 ## Model description
@@ -67,37 +69,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
 |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
-| 1.4403        | 1.0   | 1842 | 1.3829          | 46.5346 | 23.1326 | 39.4401 | 42.8272   | 17.0977 |
-| 1.3534        | 2.0   | 3684 | 1.3732          | 47.0911 | 23.5074 | 39.5951 | 43.2279   | 17.4554 |
-| 1.2795        | 3.0   | 5526 | 1.3709          | 46.8895 | 23.3243 | 39.5909 | 43.1286   | 17.2027 |
-| 1.2313        | 4.0   | 7368 | 1.3736          | 47.4946 | 23.7802 | 39.9999 | 43.5903   | 17.2198 |
-| 1.1934        | 5.0   | 9210 | 1.3772          | 47.4798 | 23.9756 | 40.0392 | 43.6545   | 17.3162 |
+| 1.4264        | 1.0   | 1842 | 1.3829          | 46.5615 | 23.1026 | 39.4012 | 42.9128   | 17.0977 |
+| 1.3527        | 2.0   | 3684 | 1.3732          | 47.1096 | 23.4582 | 39.5488 | 43.2577   | 17.4554 |
+| 1.2554        | 3.0   | 5526 | 1.3709          | 46.9079 | 23.29   | 39.5731 | 43.1779   | 17.2027 |
+| 1.2503        | 4.0   | 7368 | 1.3736          | 47.4506 | 23.7238 | 39.9803 | 43.5976   | 17.2198 |
+| 1.1675        | 5.0   | 9210 | 1.3772          | 47.4485 | 23.938  | 40.0491 | 43.6954   | 17.3162 |
 
 
 ### Framework versions
 
-- Transformers 4.26.0
+- Transformers 4.26.1
 - Pytorch 1.13.1+cu116
-- Datasets 2.9.0
+- Datasets 2.10.1
 - Tokenizers 0.13.2
-
-### Papers With Code Results
-
-As of 2 February 2023 the Papers with Code page for this task has the following leaderboard (see imgur link).
-
-Our score (Rouge 1 score of 47.4798) puts this model's performance between fourth and fifth place on the leaderboard: https://i.imgur.com/Nea77uL.jpg
-
-## Model Recycling
-
-[Evaluation on 36 datasets](https://ibm.github.io/model-recycling/model_gain_chart?avg=9.04&mnli_lp=nan&20_newsgroup=3.55&ag_news=1.66&amazon_reviews_multi=0.19&anli=14.53&boolq=16.60&cb=24.91&cola=10.35&copa=25.50&dbpedia=5.73&esnli=5.31&financial_phrasebank=19.96&imdb=0.05&isear=0.59&mnli=11.74&mrpc=15.89&multirc=5.99&poem_sentiment=23.27&qnli=3.93&qqp=5.54&rotten_tomatoes=3.54&rte=23.90&sst2=-0.14&sst_5bins=5.12&stsb=20.58&trec_coarse=4.15&trec_fine=10.93&tweet_ev_emoji=12.87&tweet_ev_emotion=6.02&tweet_ev_hate=-0.04&tweet_ev_irony=7.12&tweet_ev_offensive=2.16&tweet_ev_sentiment=-0.00&wic=12.03&wnli=9.44&wsc=9.37&yahoo_answers=3.04&model_name=andreaparker%2Fflan-t5-base-samsum&base_name=google%2Ft5-v1_1-base) using andreaparker/flan-t5-base-samsum as a base model yields average score of 77.86 in comparison to 68.82 by google/t5-v1_1-base.
-
-The model is ranked 2nd among all tested models for the google/t5-v1_1-base architecture as of 07/February/2023
-Results:
-
-|   20_newsgroup |   ag_news |   amazon_reviews_multi |    anli |   boolq |      cb |    cola |   copa |   dbpedia |   esnli |   financial_phrasebank |   imdb |   isear |    mnli |    mrpc |   multirc |   poem_sentiment |    qnli |     qqp |   rotten_tomatoes |     rte |   sst2 |   sst_5bins |    stsb |   trec_coarse |   trec_fine |   tweet_ev_emoji |   tweet_ev_emotion |   tweet_ev_hate |   tweet_ev_irony |   tweet_ev_offensive |   tweet_ev_sentiment |     wic |   wnli |     wsc |   yahoo_answers |
-|---------------:|----------:|-----------------------:|--------:|--------:|--------:|--------:|-------:|----------:|--------:|-----------------------:|-------:|--------:|--------:|--------:|----------:|-----------------:|--------:|--------:|------------------:|--------:|-------:|------------:|--------:|--------------:|------------:|-----------------:|-------------------:|----------------:|-----------------:|---------------------:|---------------------:|--------:|-------:|--------:|----------------:|
-|        86.4312 |   89.8333 |                   67.1 | 52.5937 | 82.1713 | 80.3571 | 80.5369 |     66 |      76.5 | 90.8897 |                   86.7 | 93.044 | 71.6428 | 87.2457 | 88.7255 |   62.1287 |          91.3462 | 93.3004 | 89.1393 |           89.5872 | 84.4765 | 93.578 |     56.9683 | 89.3674 |          97.4 |          93 |           46.334 |            81.6327 |         51.4815 |          74.7449 |              84.7674 |              69.8795 | 67.8683 | 56.338 | 57.6923 |            72.3 |
-
-
-For more information, see: [Model Recycling](https://ibm.github.io/model-recycling/)
-

generation_config.json

@@ -3,5 +3,5 @@
   "decoder_start_token_id": 0,
   "eos_token_id": 1,
   "pad_token_id": 0,
-  "transformers_version": "4.26.0"
+  "transformers_version": "4.26.1"
 }

pytorch_model.bin

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