diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -16,24 +16,24 @@ 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: 0.1291 -- Classification Report Lin: {'~LIN': {'precision': 0.9908008658008658, 'recall': 0.9978201634877384, 'f1-score': 0.9942981265272876, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9886609071274298, 'macro avg': {'precision': 0.4954004329004329, 'recall': 0.4989100817438692, 'f1-score': 0.4971490632636438, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817060414387628, 'recall': 0.9886609071274298, 'f1-score': 0.9851711998798988, 'support': 1852.0}} -- Hamming Lin: 0.0113 -- Classification Report Si: {'~SI': {'precision': 0.9815518176885513, 'recall': 0.9972436604189636, 'f1-score': 0.9893355209187858, 'support': 1814.0}, 'SI': {'precision': 0.4444444444444444, 'recall': 0.10526315789473684, 'f1-score': 0.1702127659574468, 'support': 38.0}, 'accuracy': 0.9789416846652268, 'macro avg': {'precision': 0.7129981310664979, 'recall': 0.5512534091568502, 'f1-score': 0.5797741434381163, 'support': 1852.0}, 'weighted avg': {'precision': 0.9705312560345145, 'recall': 0.9789416846652268, 'f1-score': 0.9725284665513285, 'support': 1852.0}} -- Hamming Si: 0.0211 -- Classification Report Cl: {'~CL': {'precision': 0.9746909947027663, 'recall': 0.9910233393177738, 'f1-score': 0.9827893175074184, 'support': 1671.0}, 'CL': {'precision': 0.9019607843137255, 'recall': 0.7624309392265194, 'f1-score': 0.8263473053892215, 'support': 181.0}, 'accuracy': 0.968682505399568, 'macro avg': {'precision': 0.9383258895082459, 'recall': 0.8767271392721465, 'f1-score': 0.90456831144832, 'support': 1852.0}, 'weighted avg': {'precision': 0.9675829125859108, 'recall': 0.968682505399568, 'f1-score': 0.9674998983965147, 'support': 1852.0}} +- Loss: 0.2185 +- Classification Report Lin: {'~LIN': {'precision': 0.990770901194354, 'recall': 0.9945504087193461, 'f1-score': 0.9926570573837368, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9854211663066955, 'macro avg': {'precision': 0.495385450597177, 'recall': 0.49727520435967304, 'f1-score': 0.4963285286918684, 'support': 1852.0}, 'weighted avg': {'precision': 0.9816763518853345, 'recall': 0.9854211663066955, 'f1-score': 0.9835451945459811, 'support': 1852.0}} +- Hamming Lin: 0.0146 +- Classification Report Si: {'~SI': {'precision': 0.9839601769911505, 'recall': 0.9807056229327453, 'f1-score': 0.9823302043070127, 'support': 1814.0}, 'SI': {'precision': 0.20454545454545456, 'recall': 0.23684210526315788, 'f1-score': 0.21951219512195122, 'support': 38.0}, 'accuracy': 0.9654427645788337, 'macro avg': {'precision': 0.5942528157683025, 'recall': 0.6087738640979516, 'f1-score': 0.600921199714482, 'support': 1852.0}, 'weighted avg': {'precision': 0.9679678662714223, 'recall': 0.9654427645788337, 'f1-score': 0.9666784309004076, 'support': 1852.0}} +- Hamming Si: 0.0346 +- Classification Report Cl: {'~CL': {'precision': 0.9775014801657785, 'recall': 0.988031119090365, 'f1-score': 0.9827380952380952, 'support': 1671.0}, 'CL': {'precision': 0.8773006134969326, 'recall': 0.7900552486187845, 'f1-score': 0.8313953488372093, 'support': 181.0}, 'accuracy': 0.968682505399568, 'macro avg': {'precision': 0.9274010468313556, 'recall': 0.8890431838545747, 'f1-score': 0.9070667220376523, 'support': 1852.0}, 'weighted avg': {'precision': 0.9677086308855078, 'recall': 0.968682505399568, 'f1-score': 0.9679470384894125, 'support': 1852.0}} - Hamming Cl: 0.0313 -- Classification Report D: {'~D': {'precision': 0.9978331527627302, 'recall': 1.0, 'f1-score': 0.9989154013015185, 'support': 1842.0}, 'D': {'precision': 1.0, 'recall': 0.6, 'f1-score': 0.75, 'support': 10.0}, 'accuracy': 0.9978401727861771, 'macro avg': {'precision': 0.9989165763813651, 'recall': 0.8, 'f1-score': 0.8744577006507592, 'support': 1852.0}, 'weighted avg': {'precision': 0.9978448528018083, 'recall': 0.9978401727861771, 'f1-score': 0.9975713656573418, 'support': 1852.0}} -- Hamming D: 0.0022 -- Classification Report Hi: {'~HI': {'precision': 0.9962203023758099, 'recall': 1.0, 'f1-score': 0.9981065728969435, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9962203023758099, 'macro avg': {'precision': 0.49811015118790497, 'recall': 0.5, 'f1-score': 0.49905328644847174, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924548908657502, 'recall': 0.9962203023758099, 'f1-score': 0.9943340318546764, 'support': 1852.0}} -- Hamming Hi: 0.0038 -- Classification Report Pl: {'~PL': {'precision': 0.9776444929116684, 'recall': 0.9950055493895672, 'f1-score': 0.9862486248624862, 'support': 1802.0}, 'PL': {'precision': 0.5, 'recall': 0.18, 'f1-score': 0.2647058823529412, 'support': 50.0}, 'accuracy': 0.9730021598272138, 'macro avg': {'precision': 0.7388222464558343, 'recall': 0.5875027746947836, 'f1-score': 0.6254772536077137, 'support': 1852.0}, 'weighted avg': {'precision': 0.9647491232326277, 'recall': 0.9730021598272138, 'f1-score': 0.9667685292223798, 'support': 1852.0}} -- Hamming Pl: 0.0270 -- Classification Report Ti: {'~TI': {'precision': 0.9742888402625821, 'recall': 0.9922005571030641, 'f1-score': 0.9831631244824731, 'support': 1795.0}, 'TI': {'precision': 0.4166666666666667, 'recall': 0.17543859649122806, 'f1-score': 0.24691358024691357, 'support': 57.0}, 'accuracy': 0.9670626349892009, 'macro avg': {'precision': 0.6954777534646244, 'recall': 0.5838195767971461, 'f1-score': 0.6150383523646934, 'support': 1852.0}, 'weighted avg': {'precision': 0.9571266027383017, 'recall': 0.9670626349892009, 'f1-score': 0.9605031763067566, 'support': 1852.0}} -- Hamming Ti: 0.0329 -- Classification Report Pc: {'~PC': {'precision': 0.9864645370871684, 'recall': 0.9978094194961665, 'f1-score': 0.9921045466920774, 'support': 1826.0}, 'PC': {'precision': 0.2, 'recall': 0.038461538461538464, 'f1-score': 0.06451612903225806, 'support': 26.0}, 'accuracy': 0.984341252699784, 'macro avg': {'precision': 0.5932322685435842, 'recall': 0.5181354789788525, 'f1-score': 0.5283103378621677, 'support': 1852.0}, 'weighted avg': {'precision': 0.9754234582727697, 'recall': 0.984341252699784, 'f1-score': 0.9790822470921016, 'support': 1852.0}} -- Hamming Pc: 0.0157 -- Global Avg: {'f1-score': 0.6404785561354858, 'hamming': 0.018156047516198703} +- Classification Report D: {'~D': {'precision': 0.9972914409534128, 'recall': 0.999457111834962, 'f1-score': 0.9983731019522777, 'support': 1842.0}, 'D': {'precision': 0.8333333333333334, 'recall': 0.5, 'f1-score': 0.625, 'support': 10.0}, 'accuracy': 0.9967602591792657, 'macro avg': {'precision': 0.915312387143373, 'recall': 0.749728555917481, 'f1-score': 0.8116865509761388, 'support': 1852.0}, 'weighted avg': {'precision': 0.9964061379965009, 'recall': 0.9967602591792657, 'f1-score': 0.9963570484860127, 'support': 1852.0}} +- Hamming D: 0.0032 +- Classification Report Hi: {'~HI': {'precision': 0.9962080173347779, 'recall': 0.9967479674796748, 'f1-score': 0.9964779192630724, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9929805615550756, 'macro avg': {'precision': 0.49810400866738896, 'recall': 0.4983739837398374, 'f1-score': 0.4982389596315362, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924426522584585, 'recall': 0.9929805615550756, 'f1-score': 0.9927115340390759, 'support': 1852.0}} +- Hamming Hi: 0.0070 +- Classification Report Pl: {'~PL': {'precision': 0.9824368825466521, 'recall': 0.9933407325194229, 'f1-score': 0.9878587196467992, 'support': 1802.0}, 'PL': {'precision': 0.6, 'recall': 0.36, 'f1-score': 0.45, 'support': 50.0}, 'accuracy': 0.9762419006479481, 'macro avg': {'precision': 0.7912184412733261, 'recall': 0.6766703662597114, 'f1-score': 0.7189293598233996, 'support': 1852.0}, 'weighted avg': {'precision': 0.9721119127154789, 'recall': 0.9762419006479481, 'f1-score': 0.9733376958982355, 'support': 1852.0}} +- Hamming Pl: 0.0238 +- Classification Report Ti: {'~TI': {'precision': 0.9827008928571429, 'recall': 0.981058495821727, 'f1-score': 0.9818790075271815, 'support': 1795.0}, 'TI': {'precision': 0.43333333333333335, 'recall': 0.45614035087719296, 'f1-score': 0.4444444444444444, 'support': 57.0}, 'accuracy': 0.964902807775378, 'macro avg': {'precision': 0.7080171130952382, 'recall': 0.7185994233494599, 'f1-score': 0.713161725985813, 'support': 1852.0}, 'weighted avg': {'precision': 0.9657927120294663, 'recall': 0.964902807775378, 'f1-score': 0.9653380949485011, 'support': 1852.0}} +- Hamming Ti: 0.0351 +- Classification Report Pc: {'~PC': {'precision': 0.9863387978142076, 'recall': 0.988499452354874, 'f1-score': 0.987417943107221, 'support': 1826.0}, 'PC': {'precision': 0.045454545454545456, 'recall': 0.038461538461538464, 'f1-score': 0.041666666666666664, 'support': 26.0}, 'accuracy': 0.9751619870410367, 'macro avg': {'precision': 0.5158966716343766, 'recall': 0.5134804954082063, 'f1-score': 0.5145423048869439, 'support': 1852.0}, 'weighted avg': {'precision': 0.9731298396277329, 'recall': 0.9751619870410367, 'f1-score': 0.9741406573688546, 'support': 1852.0}} +- Hamming Pc: 0.0248 +- Global Avg: {'f1-score': 0.6576094189684794, 'hamming': 0.021800755939524838} ## Model description @@ -53,76 +53,76 @@ More information needed The following hyperparameters were used during training: - learning_rate: 0.0001 -- train_batch_size: 256 -- eval_batch_size: 256 -- seed: 42 +- train_batch_size: 16 +- eval_batch_size: 16 +- seed: 32 - distributed_type: multi-GPU -- num_devices: 3 -- total_train_batch_size: 768 -- total_eval_batch_size: 768 +- num_devices: 4 +- total_train_batch_size: 64 +- total_eval_batch_size: 64 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 50 ### Training results -| Training Loss | Epoch | Step | Validation Loss | Classification Report Lin | Hamming Lin | Classification Report Si | Hamming Si | Classification Report Cl | Hamming Cl | Classification Report D | Hamming D | Classification Report Hi | Hamming Hi | Classification Report Pl | Hamming Pl | Classification Report Ti | Hamming Ti | Classification Report Pc | Hamming Pc | Global Avg | 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-| No log | 1.0 | 9 | 0.0937 | {'~LIN': {'precision': 0.9908207343412527, 'recall': 1.0, 'f1-score': 0.9953892053159751, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9908207343412527, 'macro avg': {'precision': 0.49541036717062636, 'recall': 0.5, 'f1-score': 0.49769460265798754, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817257276005392, 'recall': 0.9908207343412527, 'f1-score': 0.9862522633665304, 'support': 1852.0}} | 0.0092 | {'~SI': {'precision': 0.9794816414686826, 'recall': 1.0, 'f1-score': 0.9896344789961812, 'support': 1814.0}, 'SI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 38.0}, 'accuracy': 0.9794816414686826, 'macro avg': {'precision': 0.4897408207343413, 'recall': 0.5, 'f1-score': 0.4948172394980906, 'support': 1852.0}, 'weighted avg': {'precision': 0.9593842859741848, 'recall': 0.9794816414686826, 'f1-score': 0.9693288039411839, 'support': 1852.0}} | 0.0205 | {'~CL': {'precision': 0.902267818574514, 'recall': 1.0, 'f1-score': 0.94862333238717, 'support': 1671.0}, 'CL': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 181.0}, 'accuracy': 0.902267818574514, 'macro avg': {'precision': 0.451133909287257, 'recall': 0.5, 'f1-score': 0.474311666193585, 'support': 1852.0}, 'weighted avg': {'precision': 0.8140872164352121, 'recall': 0.902267818574514, 'f1-score': 0.855912304761858, 'support': 1852.0}} | 0.0977 | {'~D': {'precision': 0.9946004319654428, 'recall': 1.0, 'f1-score': 0.9972929074174337, 'support': 1842.0}, 'D': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 10.0}, 'accuracy': 0.9946004319654428, 'macro avg': {'precision': 0.4973002159827214, 'recall': 0.5, 'f1-score': 0.49864645370871685, 'support': 1852.0}, 'weighted avg': {'precision': 0.9892300192658454, 'recall': 0.9946004319654428, 'f1-score': 0.9919079565134519, 'support': 1852.0}} | 0.0054 | {'~HI': {'precision': 0.9962203023758099, 'recall': 1.0, 'f1-score': 0.9981065728969435, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9962203023758099, 'macro avg': {'precision': 0.49811015118790497, 'recall': 0.5, 'f1-score': 0.49905328644847174, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924548908657502, 'recall': 0.9962203023758099, 'f1-score': 0.9943340318546764, 'support': 1852.0}} | 0.0038 | {'~PL': {'precision': 0.9730021598272138, 'recall': 1.0, 'f1-score': 0.9863163656267104, 'support': 1802.0}, 'PL': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 50.0}, 'accuracy': 0.9730021598272138, 'macro avg': {'precision': 0.4865010799136069, 'recall': 0.5, 'f1-score': 0.4931581828133552, 'support': 1852.0}, 'weighted avg': {'precision': 0.9467332030284229, 'recall': 0.9730021598272138, 'f1-score': 0.9596879540277172, 'support': 1852.0}} | 0.0270 | {'~TI': {'precision': 0.9692224622030238, 'recall': 1.0, 'f1-score': 0.9843707156567041, 'support': 1795.0}, 'TI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 57.0}, 'accuracy': 0.9692224622030238, 'macro avg': {'precision': 0.4846112311015119, 'recall': 0.5, 'f1-score': 0.49218535782835204, 'support': 1852.0}, 'weighted avg': {'precision': 0.9393921812388919, 'recall': 0.9692224622030238, 'f1-score': 0.9540742087493432, 'support': 1852.0}} | 0.0308 | {'~PC': {'precision': 0.9859611231101512, 'recall': 1.0, 'f1-score': 0.9929309407286568, 'support': 1826.0}, 'PC': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 26.0}, 'accuracy': 0.9859611231101512, 'macro avg': {'precision': 0.4929805615550756, 'recall': 0.5, 'f1-score': 0.4964654703643284, 'support': 1852.0}, 'weighted avg': {'precision': 0.9721193362846307, 'recall': 0.9859611231101512, 'f1-score': 0.9789913054916455, 'support': 1852.0}} | 0.0140 | {'f1-score': 0.49329153243911095, 'hamming': 0.02605291576673866} | -| No log | 2.0 | 18 | 0.0887 | {'~LIN': {'precision': 0.9908207343412527, 'recall': 1.0, 'f1-score': 0.9953892053159751, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9908207343412527, 'macro avg': {'precision': 0.49541036717062636, 'recall': 0.5, 'f1-score': 0.49769460265798754, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817257276005392, 'recall': 0.9908207343412527, 'f1-score': 0.9862522633665304, 'support': 1852.0}} | 0.0092 | {'~SI': {'precision': 0.9794816414686826, 'recall': 1.0, 'f1-score': 0.9896344789961812, 'support': 1814.0}, 'SI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 38.0}, 'accuracy': 0.9794816414686826, 'macro avg': {'precision': 0.4897408207343413, 'recall': 0.5, 'f1-score': 0.4948172394980906, 'support': 1852.0}, 'weighted avg': {'precision': 0.9593842859741848, 'recall': 0.9794816414686826, 'f1-score': 0.9693288039411839, 'support': 1852.0}} | 0.0205 | {'~CL': {'precision': 0.902267818574514, 'recall': 1.0, 'f1-score': 0.94862333238717, 'support': 1671.0}, 'CL': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 181.0}, 'accuracy': 0.902267818574514, 'macro avg': {'precision': 0.451133909287257, 'recall': 0.5, 'f1-score': 0.474311666193585, 'support': 1852.0}, 'weighted avg': {'precision': 0.8140872164352121, 'recall': 0.902267818574514, 'f1-score': 0.855912304761858, 'support': 1852.0}} | 0.0977 | {'~D': {'precision': 0.9946004319654428, 'recall': 1.0, 'f1-score': 0.9972929074174337, 'support': 1842.0}, 'D': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 10.0}, 'accuracy': 0.9946004319654428, 'macro avg': {'precision': 0.4973002159827214, 'recall': 0.5, 'f1-score': 0.49864645370871685, 'support': 1852.0}, 'weighted avg': {'precision': 0.9892300192658454, 'recall': 0.9946004319654428, 'f1-score': 0.9919079565134519, 'support': 1852.0}} | 0.0054 | {'~HI': {'precision': 0.9962203023758099, 'recall': 1.0, 'f1-score': 0.9981065728969435, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9962203023758099, 'macro avg': {'precision': 0.49811015118790497, 'recall': 0.5, 'f1-score': 0.49905328644847174, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924548908657502, 'recall': 0.9962203023758099, 'f1-score': 0.9943340318546764, 'support': 1852.0}} | 0.0038 | {'~PL': {'precision': 0.9730021598272138, 'recall': 1.0, 'f1-score': 0.9863163656267104, 'support': 1802.0}, 'PL': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 50.0}, 'accuracy': 0.9730021598272138, 'macro avg': {'precision': 0.4865010799136069, 'recall': 0.5, 'f1-score': 0.4931581828133552, 'support': 1852.0}, 'weighted avg': {'precision': 0.9467332030284229, 'recall': 0.9730021598272138, 'f1-score': 0.9596879540277172, 'support': 1852.0}} | 0.0270 | {'~TI': {'precision': 0.9692224622030238, 'recall': 1.0, 'f1-score': 0.9843707156567041, 'support': 1795.0}, 'TI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 57.0}, 'accuracy': 0.9692224622030238, 'macro avg': {'precision': 0.4846112311015119, 'recall': 0.5, 'f1-score': 0.49218535782835204, 'support': 1852.0}, 'weighted avg': {'precision': 0.9393921812388919, 'recall': 0.9692224622030238, 'f1-score': 0.9540742087493432, 'support': 1852.0}} | 0.0308 | {'~PC': {'precision': 0.9859611231101512, 'recall': 1.0, 'f1-score': 0.9929309407286568, 'support': 1826.0}, 'PC': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 26.0}, 'accuracy': 0.9859611231101512, 'macro avg': {'precision': 0.4929805615550756, 'recall': 0.5, 'f1-score': 0.4964654703643284, 'support': 1852.0}, 'weighted avg': {'precision': 0.9721193362846307, 'recall': 0.9859611231101512, 'f1-score': 0.9789913054916455, 'support': 1852.0}} | 0.0140 | {'f1-score': 0.49329153243911095, 'hamming': 0.02605291576673866} | -| No log | 3.0 | 27 | 0.0852 | {'~LIN': {'precision': 0.9908207343412527, 'recall': 1.0, 'f1-score': 0.9953892053159751, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 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'accuracy': 0.9978401727861771, 'macro avg': {'precision': 0.9989165763813651, 'recall': 0.8, 'f1-score': 0.8744577006507592, 'support': 1852.0}, 'weighted avg': {'precision': 0.9978448528018083, 'recall': 0.9978401727861771, 'f1-score': 0.9975713656573418, 'support': 1852.0}} | 0.0022 | {'~HI': {'precision': 0.9962203023758099, 'recall': 1.0, 'f1-score': 0.9981065728969435, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9962203023758099, 'macro avg': {'precision': 0.49811015118790497, 'recall': 0.5, 'f1-score': 0.49905328644847174, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924548908657502, 'recall': 0.9962203023758099, 'f1-score': 0.9943340318546764, 'support': 1852.0}} | 0.0038 | {'~PL': {'precision': 0.9776444929116684, 'recall': 0.9950055493895672, 'f1-score': 0.9862486248624862, 'support': 1802.0}, 'PL': {'precision': 0.5, 'recall': 0.18, 'f1-score': 0.2647058823529412, 'support': 50.0}, 'accuracy': 0.9730021598272138, 'macro avg': {'precision': 0.7388222464558343, 'recall': 0.5875027746947836, 'f1-score': 0.6254772536077137, 'support': 1852.0}, 'weighted avg': {'precision': 0.9647491232326277, 'recall': 0.9730021598272138, 'f1-score': 0.9667685292223798, 'support': 1852.0}} | 0.0270 | {'~TI': {'precision': 0.9742888402625821, 'recall': 0.9922005571030641, 'f1-score': 0.9831631244824731, 'support': 1795.0}, 'TI': {'precision': 0.4166666666666667, 'recall': 0.17543859649122806, 'f1-score': 0.24691358024691357, 'support': 57.0}, 'accuracy': 0.9670626349892009, 'macro avg': {'precision': 0.6954777534646244, 'recall': 0.5838195767971461, 'f1-score': 0.6150383523646934, 'support': 1852.0}, 'weighted avg': {'precision': 0.9571266027383017, 'recall': 0.9670626349892009, 'f1-score': 0.9605031763067566, 'support': 1852.0}} | 0.0329 | {'~PC': {'precision': 0.9864645370871684, 'recall': 0.9978094194961665, 'f1-score': 0.9921045466920774, 'support': 1826.0}, 'PC': {'precision': 0.2, 'recall': 0.038461538461538464, 'f1-score': 0.06451612903225806, 'support': 26.0}, 'accuracy': 0.984341252699784, 'macro avg': {'precision': 0.5932322685435842, 'recall': 0.5181354789788525, 'f1-score': 0.5283103378621677, 'support': 1852.0}, 'weighted avg': {'precision': 0.9754234582727697, 'recall': 0.984341252699784, 'f1-score': 0.9790822470921016, 'support': 1852.0}} | 0.0157 | {'f1-score': 0.6402567094214586, 'hamming': 0.018156047516198703} | -| No log | 49.0 | 441 | 0.1290 | {'~LIN': {'precision': 0.9908008658008658, 'recall': 0.9978201634877384, 'f1-score': 0.9942981265272876, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9886609071274298, 'macro avg': {'precision': 0.4954004329004329, 'recall': 0.4989100817438692, 'f1-score': 0.4971490632636438, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817060414387628, 'recall': 0.9886609071274298, 'f1-score': 0.9851711998798988, 'support': 1852.0}} | 0.0113 | {'~SI': {'precision': 0.9815418023887079, 'recall': 0.9966923925027563, 'f1-score': 0.9890590809628009, 'support': 1814.0}, 'SI': {'precision': 0.4, 'recall': 0.10526315789473684, 'f1-score': 0.16666666666666666, 'support': 38.0}, 'accuracy': 0.978401727861771, 'macro avg': {'precision': 0.6907709011943539, 'recall': 0.5509777751987466, 'f1-score': 0.5778628738147338, 'support': 1852.0}, 'weighted avg': {'precision': 0.9696095191863479, 'recall': 0.978401727861771, 'f1-score': 0.972184938552837, 'support': 1852.0}} | 0.0216 | {'~CL': {'precision': 0.9741176470588235, 'recall': 0.9910233393177738, 'f1-score': 0.9824977751409077, 'support': 1671.0}, 'CL': {'precision': 0.9013157894736842, 'recall': 0.7569060773480663, 'f1-score': 0.8228228228228228, 'support': 181.0}, 'accuracy': 0.9681425485961123, 'macro avg': {'precision': 0.9377167182662538, 'recall': 0.8739647083329201, 'f1-score': 0.9026602989818653, 'support': 1852.0}, 'weighted avg': {'precision': 0.9670025627052004, 'recall': 0.9681425485961123, 'f1-score': 0.9668923937318509, 'support': 1852.0}} | 0.0319 | {'~D': {'precision': 0.9978331527627302, 'recall': 1.0, 'f1-score': 0.9989154013015185, 'support': 1842.0}, 'D': {'precision': 1.0, 'recall': 0.6, 'f1-score': 0.75, 'support': 10.0}, 'accuracy': 0.9978401727861771, 'macro avg': {'precision': 0.9989165763813651, 'recall': 0.8, 'f1-score': 0.8744577006507592, 'support': 1852.0}, 'weighted avg': {'precision': 0.9978448528018083, 'recall': 0.9978401727861771, 'f1-score': 0.9975713656573418, 'support': 1852.0}} | 0.0022 | {'~HI': {'precision': 0.9962203023758099, 'recall': 1.0, 'f1-score': 0.9981065728969435, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9962203023758099, 'macro avg': {'precision': 0.49811015118790497, 'recall': 0.5, 'f1-score': 0.49905328644847174, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924548908657502, 'recall': 0.9962203023758099, 'f1-score': 0.9943340318546764, 'support': 1852.0}} | 0.0038 | {'~PL': {'precision': 0.9776444929116684, 'recall': 0.9950055493895672, 'f1-score': 0.9862486248624862, 'support': 1802.0}, 'PL': {'precision': 0.5, 'recall': 0.18, 'f1-score': 0.2647058823529412, 'support': 50.0}, 'accuracy': 0.9730021598272138, 'macro avg': {'precision': 0.7388222464558343, 'recall': 0.5875027746947836, 'f1-score': 0.6254772536077137, 'support': 1852.0}, 'weighted avg': {'precision': 0.9647491232326277, 'recall': 0.9730021598272138, 'f1-score': 0.9667685292223798, 'support': 1852.0}} | 0.0270 | {'~TI': {'precision': 0.9742747673782156, 'recall': 0.9916434540389972, 'f1-score': 0.9828823854224186, 'support': 1795.0}, 'TI': {'precision': 0.4, 'recall': 0.17543859649122806, 'f1-score': 0.24390243902439024, 'support': 57.0}, 'accuracy': 0.9665226781857451, 'macro avg': {'precision': 0.6871373836891078, 'recall': 0.5835410252651126, 'f1-score': 0.6133924122234045, 'support': 1852.0}, 'weighted avg': {'precision': 0.9566000040193828, 'recall': 0.9665226781857451, 'f1-score': 0.9601384021909458, 'support': 1852.0}} | 0.0335 | {'~PC': {'precision': 0.9864645370871684, 'recall': 0.9978094194961665, 'f1-score': 0.9921045466920774, 'support': 1826.0}, 'PC': {'precision': 0.2, 'recall': 0.038461538461538464, 'f1-score': 0.06451612903225806, 'support': 26.0}, 'accuracy': 0.984341252699784, 'macro avg': {'precision': 0.5932322685435842, 'recall': 0.5181354789788525, 'f1-score': 0.5283103378621677, 'support': 1852.0}, 'weighted avg': {'precision': 0.9754234582727697, 'recall': 0.984341252699784, 'f1-score': 0.9790822470921016, 'support': 1852.0}} | 0.0157 | {'f1-score': 0.6397954033565949, 'hamming': 0.0183585313174946} | -| No log | 50.0 | 450 | 0.1291 | {'~LIN': {'precision': 0.9908008658008658, 'recall': 0.9978201634877384, 'f1-score': 0.9942981265272876, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9886609071274298, 'macro avg': {'precision': 0.4954004329004329, 'recall': 0.4989100817438692, 'f1-score': 0.4971490632636438, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817060414387628, 'recall': 0.9886609071274298, 'f1-score': 0.9851711998798988, 'support': 1852.0}} | 0.0113 | {'~SI': {'precision': 0.9815518176885513, 'recall': 0.9972436604189636, 'f1-score': 0.9893355209187858, 'support': 1814.0}, 'SI': {'precision': 0.4444444444444444, 'recall': 0.10526315789473684, 'f1-score': 0.1702127659574468, 'support': 38.0}, 'accuracy': 0.9789416846652268, 'macro avg': {'precision': 0.7129981310664979, 'recall': 0.5512534091568502, 'f1-score': 0.5797741434381163, 'support': 1852.0}, 'weighted avg': {'precision': 0.9705312560345145, 'recall': 0.9789416846652268, 'f1-score': 0.9725284665513285, 'support': 1852.0}} | 0.0211 | {'~CL': {'precision': 0.9746909947027663, 'recall': 0.9910233393177738, 'f1-score': 0.9827893175074184, 'support': 1671.0}, 'CL': {'precision': 0.9019607843137255, 'recall': 0.7624309392265194, 'f1-score': 0.8263473053892215, 'support': 181.0}, 'accuracy': 0.968682505399568, 'macro avg': {'precision': 0.9383258895082459, 'recall': 0.8767271392721465, 'f1-score': 0.90456831144832, 'support': 1852.0}, 'weighted avg': {'precision': 0.9675829125859108, 'recall': 0.968682505399568, 'f1-score': 0.9674998983965147, 'support': 1852.0}} | 0.0313 | {'~D': {'precision': 0.9978331527627302, 'recall': 1.0, 'f1-score': 0.9989154013015185, 'support': 1842.0}, 'D': {'precision': 1.0, 'recall': 0.6, 'f1-score': 0.75, 'support': 10.0}, 'accuracy': 0.9978401727861771, 'macro avg': {'precision': 0.9989165763813651, 'recall': 0.8, 'f1-score': 0.8744577006507592, 'support': 1852.0}, 'weighted avg': {'precision': 0.9978448528018083, 'recall': 0.9978401727861771, 'f1-score': 0.9975713656573418, 'support': 1852.0}} | 0.0022 | {'~HI': {'precision': 0.9962203023758099, 'recall': 1.0, 'f1-score': 0.9981065728969435, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9962203023758099, 'macro avg': {'precision': 0.49811015118790497, 'recall': 0.5, 'f1-score': 0.49905328644847174, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924548908657502, 'recall': 0.9962203023758099, 'f1-score': 0.9943340318546764, 'support': 1852.0}} | 0.0038 | {'~PL': {'precision': 0.9776444929116684, 'recall': 0.9950055493895672, 'f1-score': 0.9862486248624862, 'support': 1802.0}, 'PL': {'precision': 0.5, 'recall': 0.18, 'f1-score': 0.2647058823529412, 'support': 50.0}, 'accuracy': 0.9730021598272138, 'macro avg': {'precision': 0.7388222464558343, 'recall': 0.5875027746947836, 'f1-score': 0.6254772536077137, 'support': 1852.0}, 'weighted avg': {'precision': 0.9647491232326277, 'recall': 0.9730021598272138, 'f1-score': 0.9667685292223798, 'support': 1852.0}} | 0.0270 | {'~TI': {'precision': 0.9742888402625821, 'recall': 0.9922005571030641, 'f1-score': 0.9831631244824731, 'support': 1795.0}, 'TI': {'precision': 0.4166666666666667, 'recall': 0.17543859649122806, 'f1-score': 0.24691358024691357, 'support': 57.0}, 'accuracy': 0.9670626349892009, 'macro avg': {'precision': 0.6954777534646244, 'recall': 0.5838195767971461, 'f1-score': 0.6150383523646934, 'support': 1852.0}, 'weighted avg': {'precision': 0.9571266027383017, 'recall': 0.9670626349892009, 'f1-score': 0.9605031763067566, 'support': 1852.0}} | 0.0329 | {'~PC': {'precision': 0.9864645370871684, 'recall': 0.9978094194961665, 'f1-score': 0.9921045466920774, 'support': 1826.0}, 'PC': {'precision': 0.2, 'recall': 0.038461538461538464, 'f1-score': 0.06451612903225806, 'support': 26.0}, 'accuracy': 0.984341252699784, 'macro avg': {'precision': 0.5932322685435842, 'recall': 0.5181354789788525, 'f1-score': 0.5283103378621677, 'support': 1852.0}, 'weighted avg': {'precision': 0.9754234582727697, 'recall': 0.984341252699784, 'f1-score': 0.9790822470921016, 'support': 1852.0}} | 0.0157 | {'f1-score': 0.6404785561354858, 'hamming': 0.018156047516198703} | +| Training Loss | Epoch | Step | Validation Loss | Classification Report Lin | Hamming Lin | Classification Report Si | Hamming Si | Classification Report Cl | Hamming Cl | Classification Report D | Hamming D | Classification Report Hi | Hamming Hi | Classification Report Pl | Hamming Pl | Classification Report Ti | Hamming Ti | Classification Report Pc | Hamming Pc | Global Avg | +|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-----------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:----------:|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:----------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:----------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:----------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:----------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:----------:|:-----------------------------------------------------------------:| +| No log | 1.0 | 98 | 0.0810 | {'~LIN': {'precision': 0.9908207343412527, 'recall': 1.0, 'f1-score': 0.9953892053159751, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9908207343412527, 'macro avg': {'precision': 0.49541036717062636, 'recall': 0.5, 'f1-score': 0.49769460265798754, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817257276005392, 'recall': 0.9908207343412527, 'f1-score': 0.9862522633665304, 'support': 1852.0}} | 0.0092 | {'~SI': {'precision': 0.9794816414686826, 'recall': 1.0, 'f1-score': 0.9896344789961812, 'support': 1814.0}, 'SI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 38.0}, 'accuracy': 0.9794816414686826, 'macro avg': {'precision': 0.4897408207343413, 'recall': 0.5, 'f1-score': 0.4948172394980906, 'support': 1852.0}, 'weighted avg': {'precision': 0.9593842859741848, 'recall': 0.9794816414686826, 'f1-score': 0.9693288039411839, 'support': 1852.0}} | 0.0205 | {'~CL': {'precision': 0.902267818574514, 'recall': 1.0, 'f1-score': 0.94862333238717, 'support': 1671.0}, 'CL': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 181.0}, 'accuracy': 0.902267818574514, 'macro avg': {'precision': 0.451133909287257, 'recall': 0.5, 'f1-score': 0.474311666193585, 'support': 1852.0}, 'weighted avg': {'precision': 0.8140872164352121, 'recall': 0.902267818574514, 'f1-score': 0.855912304761858, 'support': 1852.0}} | 0.0977 | {'~D': {'precision': 0.9946004319654428, 'recall': 1.0, 'f1-score': 0.9972929074174337, 'support': 1842.0}, 'D': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 10.0}, 'accuracy': 0.9946004319654428, 'macro avg': {'precision': 0.4973002159827214, 'recall': 0.5, 'f1-score': 0.49864645370871685, 'support': 1852.0}, 'weighted avg': {'precision': 0.9892300192658454, 'recall': 0.9946004319654428, 'f1-score': 0.9919079565134519, 'support': 1852.0}} | 0.0054 | {'~HI': {'precision': 0.9962203023758099, 'recall': 1.0, 'f1-score': 0.9981065728969435, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9962203023758099, 'macro avg': {'precision': 0.49811015118790497, 'recall': 0.5, 'f1-score': 0.49905328644847174, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924548908657502, 'recall': 0.9962203023758099, 'f1-score': 0.9943340318546764, 'support': 1852.0}} | 0.0038 | {'~PL': {'precision': 0.9730021598272138, 'recall': 1.0, 'f1-score': 0.9863163656267104, 'support': 1802.0}, 'PL': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 50.0}, 'accuracy': 0.9730021598272138, 'macro avg': {'precision': 0.4865010799136069, 'recall': 0.5, 'f1-score': 0.4931581828133552, 'support': 1852.0}, 'weighted avg': {'precision': 0.9467332030284229, 'recall': 0.9730021598272138, 'f1-score': 0.9596879540277172, 'support': 1852.0}} | 0.0270 | {'~TI': {'precision': 0.9692224622030238, 'recall': 1.0, 'f1-score': 0.9843707156567041, 'support': 1795.0}, 'TI': 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'f1-score': 0.9953892053159751, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9908207343412527, 'macro avg': {'precision': 0.49541036717062636, 'recall': 0.5, 'f1-score': 0.49769460265798754, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817257276005392, 'recall': 0.9908207343412527, 'f1-score': 0.9862522633665304, 'support': 1852.0}} | 0.0092 | {'~SI': {'precision': 0.9794705564559697, 'recall': 0.9994487320837927, 'f1-score': 0.9893587994542974, 'support': 1814.0}, 'SI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 38.0}, 'accuracy': 0.9789416846652268, 'macro avg': {'precision': 0.48973527822798485, 'recall': 0.49972436604189635, 'f1-score': 0.4946793997271487, 'support': 1852.0}, 'weighted avg': {'precision': 0.9593734284077371, 'recall': 0.9789416846652268, 'f1-score': 0.9690587808909803, 'support': 1852.0}} | 0.0211 | {'~CL': {'precision': 0.9312465064281722, 'recall': 0.9970077797725913, 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'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9929805615550756, 'macro avg': {'precision': 0.49810400866738896, 'recall': 0.4983739837398374, 'f1-score': 0.4982389596315362, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924426522584585, 'recall': 0.9929805615550756, 'f1-score': 0.9927115340390759, 'support': 1852.0}} | 0.0070 | {'~PL': {'precision': 0.9824368825466521, 'recall': 0.9933407325194229, 'f1-score': 0.9878587196467992, 'support': 1802.0}, 'PL': {'precision': 0.6, 'recall': 0.36, 'f1-score': 0.45, 'support': 50.0}, 'accuracy': 0.9762419006479481, 'macro avg': {'precision': 0.7912184412733261, 'recall': 0.6766703662597114, 'f1-score': 0.7189293598233996, 'support': 1852.0}, 'weighted avg': {'precision': 0.9721119127154789, 'recall': 0.9762419006479481, 'f1-score': 0.9733376958982355, 'support': 1852.0}} | 0.0238 | {'~TI': {'precision': 0.9827008928571429, 'recall': 0.981058495821727, 'f1-score': 0.9818790075271815, 'support': 1795.0}, 'TI': {'precision': 0.43333333333333335, 'recall': 0.45614035087719296, 'f1-score': 0.4444444444444444, 'support': 57.0}, 'accuracy': 0.964902807775378, 'macro avg': {'precision': 0.7080171130952382, 'recall': 0.7185994233494599, 'f1-score': 0.713161725985813, 'support': 1852.0}, 'weighted avg': {'precision': 0.9657927120294663, 'recall': 0.964902807775378, 'f1-score': 0.9653380949485011, 'support': 1852.0}} | 0.0351 | {'~PC': {'precision': 0.9863387978142076, 'recall': 0.988499452354874, 'f1-score': 0.987417943107221, 'support': 1826.0}, 'PC': {'precision': 0.045454545454545456, 'recall': 0.038461538461538464, 'f1-score': 0.041666666666666664, 'support': 26.0}, 'accuracy': 0.9751619870410367, 'macro avg': {'precision': 0.5158966716343766, 'recall': 0.5134804954082063, 'f1-score': 0.5145423048869439, 'support': 1852.0}, 'weighted avg': {'precision': 0.9731298396277329, 'recall': 0.9751619870410367, 'f1-score': 0.9741406573688546, 'support': 1852.0}} | 0.0248 | {'f1-score': 0.6576094189684794, 'hamming': 0.021800755939524838} | ### Framework versions -- Transformers 4.52.3 +- Transformers 4.53.1 - Pytorch 2.6.0+cu124 - Datasets 3.5.0 - Tokenizers 0.21.1