update model card README.md

README.md

@@ -7,30 +7,34 @@ metrics:
 model-index:
 - name: t5-base-DreamBank-Generation-Act-Char
   results: []
-language:
-- en
-inference:
-  parameters:
-    max_length: 128
-widget:
-- text: "I was skating on the outdoor ice pond that used to be across the street from my house. I was not alone, but I did not recognize any of the other people who were skating around. I went through my whole repertoire of jumps, spires, and steps-some of which I can do and some of which I'm not yet sure of. They were all executed flawlessly-some I repeated, some I did only once. I seemed to know that if I went into competition, I would be sure of coming in third because there were only three contestants. Up to that time I hadn't considered it because I hadn't thought I was good enough, but now since everything was going so well, I decided to enter."
-  example_title: "Dream"
 ---
+
 <!-- 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. -->
 
 # t5-base-DreamBank-Generation-Act-Char
 
-This model is a fine-tuned version of [DReAMy-lib/t5-base-DreamBank-Generation-NER-Char](https://huggingface.co/DReAMy-lib/t5-base-DreamBank-Generation-NER-Char) on the DreamBank dataset.
-The uploaded model contains the weights of the best-performing model (see table below), tune to annotate a given
-dream report according to [Hall and Van de Castle the Activity feature](https://dreams.ucsc.edu/Coding/activities.html)
+This model is a fine-tuned version of [DReAMy-lib/t5-base-DreamBank-Generation-NER-Char](https://huggingface.co/DReAMy-lib/t5-base-DreamBank-Generation-NER-Char) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3058
+- Rouge1: 0.4708
+- Rouge2: 0.4040
+- Rougel: 0.4576
+- Rougelsum: 0.4572
 
-## Training procedure
+## Model description
+
+More information needed
+
+## Intended uses & limitations
 
-The model is trained end-to-end using a text2text solution to annotate dream reports following the Activity feature 
-from the Hall and Van de Castle scoring framework. Given a report, the model generates texts of the form 
-`[(initialiser : activity type : receiver)]`. For those cases where `initialiser` and `receiver` are the same 
-entity, the output will follow the `[(initialiser : alone : activity type)]` setting.
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
 
 ### Training hyperparameters
 
@@ -48,16 +52,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
-| No log        | 1.0   | 49   | 0.4061          | 0.3684 | 0.2537 | 0.3495 | 0.3484    |
-| No log        | 2.0   | 98   | 0.3563          | 0.4151 | 0.3185 | 0.4043 | 0.4030    |
-| No log        | 3.0   | 147  | 0.3005          | 0.4456 | 0.3588 | 0.4294 | 0.4281    |
-| No log        | 4.0   | 196  | 0.2693          | 0.4743 | 0.3903 | 0.4586 | 0.4574    |
-| No log        | 5.0   | 245  | 0.2627          | 0.4751 | 0.3939 | 0.4564 | 0.4549    |
-| No log        | 6.0   | 294  | 0.2739          | 0.4744 | 0.3920 | 0.4612 | 0.4596    |
-| No log        | 7.0   | 343  | 0.2733          | 0.4702 | 0.3940 | 0.4557 | 0.4549    |
-| No log        | 8.0   | 392  | 0.2861          | 0.4739 | 0.3950 | 0.4614 | 0.4608    |
-| No log        | 9.0   | 441  | 0.3115          | 0.4645 | 0.3868 | 0.4524 | 0.4517    |
-| No log        | 10.0  | 490  | 0.3212          | 0.4655 | 0.3886 | 0.4524 | 0.4518    |
+| No log        | 1.0   | 49   | 0.3674          | 0.4008 | 0.3122 | 0.3821 | 0.3812    |
+| No log        | 2.0   | 98   | 0.3200          | 0.4240 | 0.3433 | 0.4130 | 0.4121    |
+| No log        | 3.0   | 147  | 0.2845          | 0.4591 | 0.3883 | 0.4459 | 0.4455    |
+| No log        | 4.0   | 196  | 0.2508          | 0.4614 | 0.3930 | 0.4504 | 0.4497    |
+| No log        | 5.0   | 245  | 0.2632          | 0.4614 | 0.3929 | 0.4467 | 0.4459    |
+| No log        | 6.0   | 294  | 0.2688          | 0.4706 | 0.4036 | 0.4537 | 0.4534    |
+| No log        | 7.0   | 343  | 0.2790          | 0.4682 | 0.4043 | 0.4559 | 0.4556    |
+| No log        | 8.0   | 392  | 0.2895          | 0.4670 | 0.3972 | 0.4529 | 0.4534    |
+| No log        | 9.0   | 441  | 0.3058          | 0.4708 | 0.4040 | 0.4576 | 0.4572    |
+| No log        | 10.0  | 490  | 0.3169          | 0.4690 | 0.4001 | 0.4547 | 0.4544    |
 
 
 ### Framework versions
@@ -65,4 +69,4 @@ The following hyperparameters were used during training:
 - Transformers 4.25.1
 - Pytorch 1.12.1
 - Datasets 2.5.1
-- Tokenizers 0.12.1
+- Tokenizers 0.12.1