trainer: training complete at 2024-02-06 13:09:22.048427.

README.md

@@ -18,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the None dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.5640
-- Claim: {'precision': 0.5519765739385066, 'recall': 0.32811140121845084, 'f1-score': 0.41157205240174677, 'support': 2298.0}
-- Majorclaim: {'precision': 0.5541490857946554, 'recall': 0.701067615658363, 'f1-score': 0.6190102120974077, 'support': 1124.0}
-- O: {'precision': 0.8899137758171245, 'recall': 0.8831840796019901, 'f1-score': 0.8865361566120655, 'support': 5025.0}
-- Premise: {'precision': 0.830119375573921, 'recall': 0.9103726082578046, 'f1-score': 0.8683957732949088, 'support': 6951.0}
-- Accuracy: 0.7993
-- Macro avg: {'precision': 0.7065397027810518, 'recall': 0.7056839261841521, 'f1-score': 0.6963785486015321, 'support': 15398.0}
-- Weighted avg: {'precision': 0.7879778050681424, 'recall': 0.7993245876087803, 'f1-score': 0.7879350085702844, 'support': 15398.0}
+- Claim: {'precision': 0.5515727871250914, 'recall': 0.32811140121845084, 'f1-score': 0.4114597544338336, 'support': 2298.0}
+- Majorclaim: {'precision': 0.5547752808988764, 'recall': 0.702846975088968, 'f1-score': 0.620094191522763, 'support': 1124.0}
+- O: {'precision': 0.890270812437312, 'recall': 0.8831840796019901, 'f1-score': 0.8867132867132866, 'support': 5025.0}
+- Premise: {'precision': 0.8300970873786407, 'recall': 0.9102287440656021, 'f1-score': 0.8683181225554106, 'support': 6951.0}
+- Accuracy: 0.7994
+- Macro avg: {'precision': 0.7066789919599802, 'recall': 0.7060927999937527, 'f1-score': 0.6966463388063234, 'support': 15398.0}
+- Weighted avg: {'precision': 0.7880697082354996, 'recall': 0.7993895311079361, 'f1-score': 0.7880201274566476, 'support': 15398.0}
 
 ## Model description
 
@@ -57,7 +57,7 @@ The following hyperparameters were used during training:
 |:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
 | No log        | 1.0   | 36   | 0.7525          | {'precision': 0.41766381766381766, 'recall': 0.31897302001740646, 'f1-score': 0.36170737725141877, 'support': 2298.0} | {'precision': 0.43548387096774194, 'recall': 0.02402135231316726, 'f1-score': 0.045531197301854974, 'support': 1124.0} | {'precision': 0.7476681394207167, 'recall': 0.9092537313432836, 'f1-score': 0.8205818965517241, 'support': 5025.0} | {'precision': 0.8187416331994646, 'recall': 0.8798733995108617, 'f1-score': 0.8482074752097636, 'support': 6951.0} | 0.7433   | {'precision': 0.6048893653129352, 'recall': 0.5330303757961797, 'f1-score': 0.5190069865786904, 'support': 15398.0} | {'precision': 0.707714041883217, 'recall': 0.7432783478373814, 'f1-score': 0.7079942076273884, 'support': 15398.0}  |
 | No log        | 2.0   | 72   | 0.6577          | {'precision': 0.4793814432989691, 'recall': 0.3237597911227154, 'f1-score': 0.38649350649350644, 'support': 2298.0}   | {'precision': 0.41677503250975295, 'recall': 0.5702846975088968, 'f1-score': 0.48159278737791134, 'support': 1124.0}   | {'precision': 0.7966573816155988, 'recall': 0.9106467661691542, 'f1-score': 0.849846782431052, 'support': 5025.0}  | {'precision': 0.8743144424131627, 'recall': 0.8256365990504964, 'f1-score': 0.8492785793562707, 'support': 6951.0} | 0.7598   | {'precision': 0.6417820749593709, 'recall': 0.6575819634628157, 'f1-score': 0.6418029139146851, 'support': 15398.0} | {'precision': 0.7566331163186304, 'recall': 0.7598389401220937, 'f1-score': 0.7535581151939423, 'support': 15398.0} |
-| No log        | 3.0   | 108  | 0.5640          | {'precision': 0.5519765739385066, 'recall': 0.32811140121845084, 'f1-score': 0.41157205240174677, 'support': 2298.0}  | {'precision': 0.5541490857946554, 'recall': 0.701067615658363, 'f1-score': 0.6190102120974077, 'support': 1124.0}      | {'precision': 0.8899137758171245, 'recall': 0.8831840796019901, 'f1-score': 0.8865361566120655, 'support': 5025.0} | {'precision': 0.830119375573921, 'recall': 0.9103726082578046, 'f1-score': 0.8683957732949088, 'support': 6951.0}  | 0.7993   | {'precision': 0.7065397027810518, 'recall': 0.7056839261841521, 'f1-score': 0.6963785486015321, 'support': 15398.0} | {'precision': 0.7879778050681424, 'recall': 0.7993245876087803, 'f1-score': 0.7879350085702844, 'support': 15398.0} |
+| No log        | 3.0   | 108  | 0.5640          | {'precision': 0.5515727871250914, 'recall': 0.32811140121845084, 'f1-score': 0.4114597544338336, 'support': 2298.0}   | {'precision': 0.5547752808988764, 'recall': 0.702846975088968, 'f1-score': 0.620094191522763, 'support': 1124.0}       | {'precision': 0.890270812437312, 'recall': 0.8831840796019901, 'f1-score': 0.8867132867132866, 'support': 5025.0}  | {'precision': 0.8300970873786407, 'recall': 0.9102287440656021, 'f1-score': 0.8683181225554106, 'support': 6951.0} | 0.7994   | {'precision': 0.7066789919599802, 'recall': 0.7060927999937527, 'f1-score': 0.6966463388063234, 'support': 15398.0} | {'precision': 0.7880697082354996, 'recall': 0.7993895311079361, 'f1-score': 0.7880201274566476, 'support': 15398.0} |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:e6b2738d3378b9b50f20c4d7b4b614d0d6722e256ae15eb5409460353d6e1373
 size 592330980