fuhakiem/hin-v002-trainer

README.md

@@ -16,16 +16,18 @@ model-index:
 <!-- 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/health-info-needs/huggingface/runs/3v2h15j8)
+[<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/health-info-needs/huggingface/runs/61fo8jxb)
 # results
 
 This model is a fine-tuned version of [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2402
-- Accuracy: 0.9120
-- Precision: [0.7254665863937387, 0.99392177589852]
-- Recall: [0.9812703583061889, 0.8918662556319659]
-- F1: 0.9162
+- Loss: 0.2684
+- Accuracy: 0.8979
+- Precision: 0.9260
+- Precision Per Class: [0.693325661680092, 0.993795521985433]
+- Recall: 0.8979
+- Recall Per Class: [0.9812703583061889, 0.8736068294996443]
+- F1: 0.9034
 
 ## Model description
 
@@ -55,18 +57,18 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision                                | Recall                                   | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------------------------------:|:----------------------------------------:|:------:|
-| 0.2866        | 1.0   | 307  | 0.2402          | 0.9120   | [0.7254665863937387, 0.99392177589852]   | [0.9812703583061889, 0.8918662556319659] | 0.9162 |
-| 0.2112        | 2.0   | 614  | 0.2482          | 0.8931   | [0.6824858757062147, 0.9945578231292517] | [0.9837133550488599, 0.8667299027744843] | 0.8991 |
-| 0.1771        | 3.0   | 921  | 0.4959          | 0.8343   | [0.5773244781783681, 0.9967036260113875] | [0.991042345276873, 0.7887123547545648]  | 0.8465 |
-| 0.1012        | 4.0   | 1228 | 0.5373          | 0.8496   | [0.6012877662209014, 0.9959136018680678] | [0.988599348534202, 0.8091059995257291]  | 0.8601 |
-| 0.1251        | 5.0   | 1535 | 0.5214          | 0.8542   | [0.6088264794383149, 0.9959432048681541] | [0.988599348534202, 0.8150343846336258]  | 0.8642 |
-| 0.0967        | 6.0   | 1842 | 0.7377          | 0.8259   | [0.5651769087523277, 0.9957537154989384] | [0.988599348534202, 0.7785155323689827]  | 0.8390 |
-| 0.0333        | 7.0   | 2149 | 0.7224          | 0.8457   | [0.5949119373776908, 0.9964716259923552] | [0.990228013029316, 0.8036518852264644]  | 0.8567 |
-| 0.072         | 8.0   | 2456 | 0.7021          | 0.8496   | [0.6013882002974715, 0.9956242707117853] | [0.987785016286645, 0.8093431349300451]  | 0.8601 |
-| 0.0385        | 9.0   | 2763 | 0.8352          | 0.8408   | [0.587409200968523, 0.9955621301775148]  | [0.987785016286645, 0.7979606355228835]  | 0.8522 |
-| 0.0084        | 10.0  | 3070 | 0.7899          | 0.8531   | [0.6071071071071071, 0.9956483899042646] | [0.987785016286645, 0.8138487076120465]  | 0.8632 |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Precision Per Class                      | Recall | Recall Per Class                         | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:----------------------------------------:|:------:|:----------------------------------------:|:------:|
+| 0.2734        | 1.0   | 307  | 0.2684          | 0.8979   | 0.9260    | [0.693325661680092, 0.993795521985433]   | 0.8979 | [0.9812703583061889, 0.8736068294996443] | 0.9034 |
+| 0.2102        | 2.0   | 614  | 0.2506          | 0.8896   | 0.9227    | [0.6750418760469011, 0.99480021893815]   | 0.8896 | [0.9845276872964169, 0.861987194688167]  | 0.8960 |
+| 0.1805        | 3.0   | 921  | 0.4546          | 0.8426   | 0.9050    | [0.5899175957343674, 0.9967474866942637] | 0.8426 | [0.991042345276873, 0.7993834479487788]  | 0.8539 |
+| 0.1068        | 4.0   | 1228 | 0.5444          | 0.8465   | 0.9056    | [0.5963618485742379, 0.9956024626209323] | 0.8465 | [0.987785016286645, 0.8053118330566753]  | 0.8573 |
+| 0.1227        | 5.0   | 1535 | 0.5583          | 0.8485   | 0.9067    | [0.5994079921065614, 0.9961966062024575] | 0.8485 | [0.989413680781759, 0.8074460516955181]  | 0.8592 |
+| 0.0663        | 6.0   | 1842 | 0.7334          | 0.8373   | 0.9027    | [0.5818965517241379, 0.9961274947870122] | 0.8373 | [0.989413680781759, 0.7929807920322505]  | 0.8491 |
+| 0.0342        | 7.0   | 2149 | 0.8487          | 0.8323   | 0.9002    | [0.574750830564784, 0.9949071300179748]  | 0.8323 | [0.9861563517915309, 0.7875266777329856] | 0.8447 |
+| 0.0832        | 8.0   | 2456 | 0.7713          | 0.8397   | 0.9029    | [0.5857902368293861, 0.995260663507109]  | 0.8397 | [0.9869706840390879, 0.7967749585013042] | 0.8512 |
+| 0.0308        | 9.0   | 2763 | 0.8480          | 0.8432   | 0.9040    | [0.59130859375, 0.9949955843391227]      | 0.8432 | [0.9861563517915309, 0.8015176665876216] | 0.8543 |
+| 0.0115        | 10.0  | 3070 | 0.8434          | 0.8503   | 0.9062    | [0.6029925187032419, 0.9944767441860465] | 0.8503 | [0.9845276872964169, 0.8112402181645719] | 0.8607 |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:d4f6f470565370ee4e5931ae6f2a330e4ef4ce28208724db843406e2f6bc87b1
 size 133466376