Update README.md

README.md

@@ -10,6 +10,10 @@ metrics:
 model-index:
 - name: fedcsis-slot_baseline-xlm_r-es
   results: []
+datasets:
+- cartesinus/leyzer-fedcsis
+language:
+- es
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -17,7 +21,15 @@ should probably proofread and complete it, then remove this comment. -->
 
 # fedcsis-slot_baseline-xlm_r-es
 
-This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the 
+[leyzer-fedcsis](https://huggingface.co/cartesinus/leyzer-fedcsis) dataset.
+
+Result on test set:
+- Precision: 0.9696
+- Recall: 0.9686
+- F1: 0.9691
+- Accuracy: 0.9904
+
 It achieves the following results on the evaluation set:
 - Loss: 0.0521
 - Precision: 0.9728
@@ -65,10 +77,69 @@ The following hyperparameters were used during training:
 | 0.01          | 9.0   | 8469 | 0.0500          | 0.9720    | 0.9702 | 0.9711 | 0.9913   |
 | 0.0072        | 10.0  | 9410 | 0.0521          | 0.9728    | 0.9711 | 0.9720 | 0.9914   |
 
+### Per slot evaluation
+
+| slot_name | precision | recall | f1 | tc_size |
+|-----------|-----------|--------|----|---------|
+| album | 0.9500 | 0.9135 | 0.9314 | 104 |
+| all_lang | 0.7500 | 1.0000 | 0.8571 | 3 |
+| artist | 0.9556 | 0.9685 | 0.9620 | 222 |
+| av_alias | 1.0000 | 1.0000 | 1.0000 | 18 |
+| caption | 0.9565 | 0.9362 | 0.9462 | 47 |
+| category | 0.9091 | 1.0000 | 0.9524 | 10 |
+| channel | 0.7857 | 0.7857 | 0.7857 | 14 |
+| channel_id | 0.9500 | 1.0000 | 0.9744 | 19 |
+| count | 1.0000 | 1.0000 | 1.0000 | 8 |
+| date | 0.9762 | 0.9762 | 0.9762 | 42 |
+| date_day | 1.0000 | 1.0000 | 1.0000 | 6 |
+| date_month | 1.0000 | 1.0000 | 1.0000 | 7 |
+| device_name | 0.9770 | 1.0000 | 0.9884 | 85 |
+| email | 1.0000 | 0.9740 | 0.9868 | 192 |
+| event_name | 1.0000 | 1.0000 | 1.0000 | 35 |
+| file_name | 1.0000 | 1.0000 | 1.0000 | 10 |
+| file_size | 1.0000 | 1.0000 | 1.0000 | 2 |
+| filter | 1.0000 | 1.0000 | 1.0000 | 15 |
+| hashtag | 1.0000 | 0.9565 | 0.9778 | 46 |
+| img_query | 0.9843 | 0.9843 | 0.9843 | 764 |
+| label | 1.0000 | 1.0000 | 1.0000 | 7 |
+| location | 0.9753 | 0.9875 | 0.9814 | 80 |
+| mail | 1.0000 | 1.0000 | 1.0000 | 5 |
+| message | 0.9577 | 0.9607 | 0.9592 | 636 |
+| mime_type | 1.0000 | 1.0000 | 1.0000 | 1 |
+| name | 0.9677 | 0.9677 | 0.9677 | 31 |
+| percent | 0.8571 | 1.0000 | 0.9231 | 6 |
+| phone_number | 0.9429 | 0.9763 | 0.9593 | 169 |
+| phone_type | 1.0000 | 0.6667 | 0.8000 | 3 |
+| picture_url | 1.0000 | 0.9286 | 0.9630 | 42 |
+| playlist | 0.9701 | 0.9630 | 0.9665 | 135 |
+| portal | 1.0000 | 0.9940 | 0.9970 | 168 |
+| priority | 1.0000 | 1.0000 | 1.0000 | 3 |
+| purpose | 0.0000 | 0.0000 | 0.0000 | 1 |
+| query | 0.9259 | 0.8929 | 0.9091 | 28 |
+| rating | 1.0000 | 1.0000 | 1.0000 | 3 |
+| review_count | 0.7500 | 0.7500 | 0.7500 | 4 |
+| section | 1.0000 | 1.0000 | 1.0000 | 134 |
+| seek_time | 1.0000 | 1.0000 | 1.0000 | 2 |
+| sender | 0.0000 | 0.0000 | 0.0000 | 1 |
+| sender_address | 1.0000 | 1.0000 | 1.0000 | 6 |
+| song | 0.9314 | 0.9628 | 0.9468 | 296 |
+| src_lang | 0.9872 | 1.0000 | 0.9935 | 77 |
+| status | 0.8462 | 0.9565 | 0.8980 | 23 |
+| subject | 0.9555 | 0.9567 | 0.9561 | 785 |
+| text | 0.9798 | 0.9798 | 0.9798 | 99 |
+| time | 1.0000 | 1.0000 | 1.0000 | 32 |
+| to | 0.9760 | 0.9651 | 0.9705 | 802 |
+| topic | 1.0000 | 1.0000 | 1.0000 | 1 |
+| translator | 1.0000 | 1.0000 | 1.0000 | 52 |
+| trg_lang | 0.9886 | 1.0000 | 0.9943 | 87 |
+| txt_query | 1.0000 | 0.8947 | 0.9444 | 19 |
+| username | 1.0000 | 1.0000 | 1.0000 | 6 |
+| value | 0.9318 | 0.9535 | 0.9425 | 43 |
+| weight | 1.0000 | 1.0000 | 1.0000 | 1 |
 
 ### Framework versions
 
 - Transformers 4.27.4
 - Pytorch 1.13.1+cu116
 - Datasets 2.11.0
-- Tokenizers 0.13.2
+- Tokenizers 0.13.2