End of training

README.md

@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1851
-- Classification Report: {'0': {'precision': 0.9412477286493035, 'recall': 0.9761306532663316, 'f1-score': 0.9583718778908418, 'support': 1592.0}, '1': {'precision': 0.8109452736318408, 'recall': 0.6269230769230769, 'f1-score': 0.7071583514099783, 'support': 260.0}, 'accuracy': 0.9271058315334774, 'macro avg': {'precision': 0.8760965011405721, 'recall': 0.8015268650947043, 'f1-score': 0.83276511465041, 'support': 1852.0}, 'weighted avg': {'precision': 0.9229547274049513, 'recall': 0.9271058315334774, 'f1-score': 0.9231043201775456, 'support': 1852.0}}
+- Loss: 0.1836
+- Classification Report: {'0': {'precision': 0.9434650455927052, 'recall': 0.9748743718592965, 'f1-score': 0.9589125733704047, 'support': 1592.0}, '1': {'precision': 0.8067632850241546, 'recall': 0.6423076923076924, 'f1-score': 0.715203426124197, 'support': 260.0}, 'accuracy': 0.9281857451403888, 'macro avg': {'precision': 0.8751141653084299, 'recall': 0.8085910320834944, 'f1-score': 0.8370579997473009, 'support': 1852.0}, 'weighted avg': {'precision': 0.9242736537202305, 'recall': 0.9281857451403888, 'f1-score': 0.9246985462192091, 'support': 1852.0}}
 
 ## Model description
 
@@ -48,11 +48,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Classification Report                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
 |:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
-| No log        | 1.0   | 98   | 0.2211          | {'0': {'precision': 0.9382716049382716, 'recall': 0.9547738693467337, 'f1-score': 0.9464508094645081, 'support': 1592.0}, '1': {'precision': 0.6896551724137931, 'recall': 0.6153846153846154, 'f1-score': 0.6504065040650406, 'support': 260.0}, 'accuracy': 0.9071274298056156, 'macro avg': {'precision': 0.8139633886760324, 'recall': 0.7850792423656745, 'f1-score': 0.7984286567647744, 'support': 1852.0}, 'weighted avg': {'precision': 0.9033686500482261, 'recall': 0.9071274298056156, 'f1-score': 0.9048895138900688, 'support': 1852.0}} |
-| No log        | 2.0   | 196  | 0.2076          | {'0': {'precision': 0.9136231884057971, 'recall': 0.9899497487437185, 'f1-score': 0.9502562556526982, 'support': 1592.0}, '1': {'precision': 0.8740157480314961, 'recall': 0.4269230769230769, 'f1-score': 0.5736434108527132, 'support': 260.0}, 'accuracy': 0.9109071274298056, 'macro avg': {'precision': 0.8938194682186467, 'recall': 0.7084364128333978, 'f1-score': 0.7619498332527057, 'support': 1852.0}, 'weighted avg': {'precision': 0.9080627486124287, 'recall': 0.9109071274298056, 'f1-score': 0.8973840420198709, 'support': 1852.0}} |
-| No log        | 3.0   | 294  | 0.1986          | {'0': {'precision': 0.96248382923674, 'recall': 0.9346733668341709, 'f1-score': 0.9483747609942639, 'support': 1592.0}, '1': {'precision': 0.6601307189542484, 'recall': 0.7769230769230769, 'f1-score': 0.7137809187279152, 'support': 260.0}, 'accuracy': 0.9125269978401728, 'macro avg': {'precision': 0.8113072740954942, 'recall': 0.855798221878624, 'f1-score': 0.8310778398610895, 'support': 1852.0}, 'weighted avg': {'precision': 0.9200368483115523, 'recall': 0.9125269978401728, 'f1-score': 0.9154404202873251, 'support': 1852.0}}    |
-| No log        | 4.0   | 392  | 0.1968          | {'0': {'precision': 0.9618863049095607, 'recall': 0.9353015075376885, 'f1-score': 0.9484076433121019, 'support': 1592.0}, '1': {'precision': 0.6611842105263158, 'recall': 0.7730769230769231, 'f1-score': 0.7127659574468085, 'support': 260.0}, 'accuracy': 0.9125269978401728, 'macro avg': {'precision': 0.8115352577179382, 'recall': 0.8541892153073058, 'f1-score': 0.8305868003794552, 'support': 1852.0}, 'weighted avg': {'precision': 0.9196711080739, 'recall': 0.9125269978401728, 'f1-score': 0.9153261971323092, 'support': 1852.0}}    |
-| No log        | 5.0   | 490  | 0.1851          | {'0': {'precision': 0.9412477286493035, 'recall': 0.9761306532663316, 'f1-score': 0.9583718778908418, 'support': 1592.0}, '1': {'precision': 0.8109452736318408, 'recall': 0.6269230769230769, 'f1-score': 0.7071583514099783, 'support': 260.0}, 'accuracy': 0.9271058315334774, 'macro avg': {'precision': 0.8760965011405721, 'recall': 0.8015268650947043, 'f1-score': 0.83276511465041, 'support': 1852.0}, 'weighted avg': {'precision': 0.9229547274049513, 'recall': 0.9271058315334774, 'f1-score': 0.9231043201775456, 'support': 1852.0}}   |
+| No log        | 1.0   | 98   | 0.2189          | {'0': {'precision': 0.9206631142687981, 'recall': 0.9767587939698492, 'f1-score': 0.9478817433709235, 'support': 1592.0}, '1': {'precision': 0.7730061349693251, 'recall': 0.4846153846153846, 'f1-score': 0.5957446808510638, 'support': 260.0}, 'accuracy': 0.9076673866090713, 'macro avg': {'precision': 0.8468346246190617, 'recall': 0.7306870892926169, 'f1-score': 0.7718132121109936, 'support': 1852.0}, 'weighted avg': {'precision': 0.8999337327256756, 'recall': 0.9076673866090713, 'f1-score': 0.8984456546802305, 'support': 1852.0}} |
+| No log        | 2.0   | 196  | 0.2076          | {'0': {'precision': 0.9115606936416185, 'recall': 0.9905778894472361, 'f1-score': 0.9494280553883203, 'support': 1592.0}, '1': {'precision': 0.8770491803278688, 'recall': 0.4115384615384615, 'f1-score': 0.5602094240837696, 'support': 260.0}, 'accuracy': 0.9092872570194385, 'macro avg': {'precision': 0.8943049369847437, 'recall': 0.7010581754928489, 'f1-score': 0.754818739736045, 'support': 1852.0}, 'weighted avg': {'precision': 0.9067156647746775, 'recall': 0.9092872570194385, 'f1-score': 0.8947861309071199, 'support': 1852.0}}  |
+| No log        | 3.0   | 294  | 0.1875          | {'0': {'precision': 0.9410692588092345, 'recall': 0.9729899497487438, 'f1-score': 0.9567634342186535, 'support': 1592.0}, '1': {'precision': 0.7912621359223301, 'recall': 0.6269230769230769, 'f1-score': 0.6995708154506438, 'support': 260.0}, 'accuracy': 0.9244060475161987, 'macro avg': {'precision': 0.8661656973657823, 'recall': 0.7999565133359103, 'f1-score': 0.8281671248346487, 'support': 1852.0}, 'weighted avg': {'precision': 0.9200380212549175, 'recall': 0.9244060475161987, 'f1-score': 0.9206564791000345, 'support': 1852.0}} |
+| No log        | 4.0   | 392  | 0.1924          | {'0': {'precision': 0.9565772669220945, 'recall': 0.9409547738693468, 'f1-score': 0.9487017099430018, 'support': 1592.0}, '1': {'precision': 0.6713286713286714, 'recall': 0.7384615384615385, 'f1-score': 0.7032967032967034, 'support': 260.0}, 'accuracy': 0.9125269978401728, 'macro avg': {'precision': 0.813952969125383, 'recall': 0.8397081561654427, 'f1-score': 0.8259992066198526, 'support': 1852.0}, 'weighted avg': {'precision': 0.9165315677567111, 'recall': 0.9125269978401728, 'f1-score': 0.9142496031784026, 'support': 1852.0}}  |
+| No log        | 5.0   | 490  | 0.1836          | {'0': {'precision': 0.9434650455927052, 'recall': 0.9748743718592965, 'f1-score': 0.9589125733704047, 'support': 1592.0}, '1': {'precision': 0.8067632850241546, 'recall': 0.6423076923076924, 'f1-score': 0.715203426124197, 'support': 260.0}, 'accuracy': 0.9281857451403888, 'macro avg': {'precision': 0.8751141653084299, 'recall': 0.8085910320834944, 'f1-score': 0.8370579997473009, 'support': 1852.0}, 'weighted avg': {'precision': 0.9242736537202305, 'recall': 0.9281857451403888, 'f1-score': 0.9246985462192091, 'support': 1852.0}}  |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:4a7a838018ae6002bc8a1d17df5fb627eb2d14daa30b57af9d114d923144ab56
 size 1583351632