Training in progress, step 570

README.md

@@ -74,31 +74,31 @@ model-index:
       type: chess-ir
     metrics:
     - type: cosine_accuracy@1
-      value: 0.02
+      value: 0.01
       name: Cosine Accuracy@1
     - type: cosine_accuracy@10
-      value: 0.135
+      value: 0.06
       name: Cosine Accuracy@10
     - type: cosine_precision@1
-      value: 0.02
+      value: 0.01
       name: Cosine Precision@1
     - type: cosine_precision@10
-      value: 0.0175
+      value: 0.006999999999999999
       name: Cosine Precision@10
     - type: cosine_recall@1
-      value: 0.006666666666666666
+      value: 0.003333333333333333
       name: Cosine Recall@1
     - type: cosine_recall@10
-      value: 0.05833333333333333
+      value: 0.02333333333333333
       name: Cosine Recall@10
     - type: cosine_ndcg@10
-      value: 0.040260232965004236
+      value: 0.0165414546823231
       name: Cosine Ndcg@10
     - type: cosine_mrr@10
-      value: 0.05090277777777777
+      value: 0.021797619047619052
       name: Cosine Mrr@10
     - type: cosine_map@100
-      value: 0.03468285594907049
+      value: 0.01826039464782554
       name: Cosine Map@100
   - task:
       type: information-retrieval
@@ -108,31 +108,31 @@ model-index:
       type: chess-ir-tokens
     metrics:
     - type: cosine_accuracy@1
-      value: 0.1111111111111111
+      value: 0.05291005291005291
       name: Cosine Accuracy@1
     - type: cosine_accuracy@10
-      value: 0.30158730158730157
+      value: 0.21164021164021163
       name: Cosine Accuracy@10
     - type: cosine_precision@1
-      value: 0.1111111111111111
+      value: 0.05291005291005291
       name: Cosine Precision@1
     - type: cosine_precision@10
-      value: 0.0835978835978836
+      value: 0.056613756613756616
       name: Cosine Precision@10
     - type: cosine_recall@1
-      value: 0.008191309640952804
+      value: 0.0032049522325313766
       name: Cosine Recall@1
     - type: cosine_recall@10
-      value: 0.03797928598263959
+      value: 0.023108435943979263
       name: Cosine Recall@10
     - type: cosine_ndcg@10
-      value: 0.0963937043281825
+      value: 0.062386658509055025
       name: Cosine Ndcg@10
     - type: cosine_mrr@10
-      value: 0.16048962794994542
+      value: 0.09312379272696733
       name: Cosine Mrr@10
     - type: cosine_map@100
-      value: 0.05480807151213741
+      value: 0.0369514194632888
       name: Cosine Map@100
 ---
 
@@ -199,7 +199,7 @@ print(query_embeddings.shape, document_embeddings.shape)
 # Get the similarity scores for the embeddings
 similarities = model.similarity(query_embeddings, document_embeddings)
 print(similarities)
-# tensor([[ 0.8014, -0.0485,  0.0709]])
+# tensor([[ 0.9564, -0.1107,  0.0607]])
 ```
 <!--
 ### Direct Usage (Transformers)
@@ -236,15 +236,15 @@ You can finetune this model on your own dataset.
 
 | Metric              | chess-ir   | chess-ir-tokens |
 |:--------------------|:-----------|:----------------|
-| cosine_accuracy@1   | 0.02       | 0.1111          |
-| cosine_accuracy@10  | 0.135      | 0.3016          |
-| cosine_precision@1  | 0.02       | 0.1111          |
-| cosine_precision@10 | 0.0175     | 0.0836          |
-| cosine_recall@1     | 0.0067     | 0.0082          |
-| cosine_recall@10    | 0.0583     | 0.038           |
-| **cosine_ndcg@10**  | **0.0403** | **0.0964**      |
-| cosine_mrr@10       | 0.0509     | 0.1605          |
-| cosine_map@100      | 0.0347     | 0.0548          |
+| cosine_accuracy@1   | 0.01       | 0.0529          |
+| cosine_accuracy@10  | 0.06       | 0.2116          |
+| cosine_precision@1  | 0.01       | 0.0529          |
+| cosine_precision@10 | 0.007      | 0.0566          |
+| cosine_recall@1     | 0.0033     | 0.0032          |
+| cosine_recall@10    | 0.0233     | 0.0231          |
+| **cosine_ndcg@10**  | **0.0165** | **0.0624**      |
+| cosine_mrr@10       | 0.0218     | 0.0931          |
+| cosine_map@100      | 0.0183     | 0.037           |
 
 <!--
 ## Bias, Risks and Limitations
@@ -434,12 +434,23 @@ You can finetune this model on your own dataset.
 | 0.0815 | 232  | 7.3665        | -                       | -                              |
 | 0.0916 | 261  | 7.0534        | -                       | -                              |
 | 0.1001 | 285  | -             | 0.0403                  | 0.0964                         |
+| 0.1018 | 290  | 6.8225        | -                       | -                              |
+| 0.1120 | 319  | 6.6948        | -                       | -                              |
+| 0.1222 | 348  | 6.6811        | -                       | -                              |
+| 0.1324 | 377  | 6.5559        | -                       | -                              |
+| 0.1426 | 406  | 6.6007        | -                       | -                              |
+| 0.1527 | 435  | 6.5704        | -                       | -                              |
+| 0.1629 | 464  | 6.4524        | -                       | -                              |
+| 0.1731 | 493  | 6.4562        | -                       | -                              |
+| 0.1833 | 522  | 6.5016        | -                       | -                              |
+| 0.1935 | 551  | 6.4405        | -                       | -                              |
+| 0.2001 | 570  | -             | 0.0165                  | 0.0624                         |
 
 
 ### Training Time
-- **Training**: 16.5 seconds
+- **Training**: 33.1 seconds
 - **Evaluation**: 0.1 seconds
-- **Total**: 16.6 seconds
+- **Total**: 33.2 seconds
 
 ### Framework Versions
 - Python: 3.12.10

eval/Information-Retrieval_evaluation_chess-ir-tokens_results.csv

@@ -1,2 +1,3 @@
 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
 0.10007022471910113,285,0.1111111111111111,0.30158730158730157,0.1111111111111111,0.008191309640952804,0.0835978835978836,0.03797928598263959,0.16048962794994542,0.0963937043281825,0.05480807151213741
+0.20014044943820225,570,0.05291005291005291,0.21164021164021163,0.05291005291005291,0.0032049522325313766,0.056613756613756616,0.023108435943979263,0.09312379272696733,0.062386658509055025,0.0369514194632888

eval/Information-Retrieval_evaluation_chess-ir_results.csv

@@ -1,2 +1,3 @@
 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@10,cosine-Recall@10,cosine-MRR@10,cosine-NDCG@10,cosine-MAP@100
 0.10007022471910113,285,0.02,0.135,0.02,0.006666666666666666,0.0175,0.05833333333333333,0.05090277777777777,0.040260232965004236,0.03468285594907049
+0.20014044943820225,570,0.01,0.06,0.01,0.003333333333333333,0.006999999999999999,0.02333333333333333,0.021797619047619052,0.0165414546823231,0.01826039464782554

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c50ae1fdd13646f6ccd8502b934c8d7f1ac91ee33935efefe06cbb8bd4c6cdd4
+oid sha256:7dc6e93a2832d52718e604d16e60ed4d6898b4984a79af56244b878f9f9eba05
 size 8880224