End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: microsoft/deberta-base
+tags:
+- generated_from_trainer
+model-index:
+- name: emotion_classifier
+  results: []
+---
+
+<!-- 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. -->
+
+# emotion_classifier
+
+This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0901
+- Exact Match Accuracy: 0.4616
+- Precision Micro: 0.6252
+- Recall Micro: 0.5498
+- F1 Micro: 0.5851
+- Precision Macro: 0.5584
+- Recall Macro: 0.4443
+- F1 Macro: 0.4783
+- Classification Report: {'admiration': {'precision': 0.7021739130434783, 'recall': 0.6408730158730159, 'f1-score': 0.6701244813278008, 'support': 504.0}, 'amusement': {'precision': 0.7582781456953642, 'recall': 0.8674242424242424, 'f1-score': 0.8091872791519434, 'support': 264.0}, 'anger': {'precision': 0.5073891625615764, 'recall': 0.5202020202020202, 'f1-score': 0.513715710723192, 'support': 198.0}, 'annoyance': {'precision': 0.375886524822695, 'recall': 0.33125, 'f1-score': 0.3521594684385382, 'support': 320.0}, 'approval': {'precision': 0.5150214592274678, 'recall': 0.3418803418803419, 'f1-score': 0.410958904109589, 'support': 351.0}, 'caring': {'precision': 0.639344262295082, 'recall': 0.28888888888888886, 'f1-score': 0.3979591836734694, 'support': 135.0}, 'confusion': {'precision': 0.5686274509803921, 'recall': 0.3790849673202614, 'f1-score': 0.4549019607843137, 'support': 153.0}, 'curiosity': {'precision': 0.487012987012987, 'recall': 0.528169014084507, 'f1-score': 0.5067567567567568, 'support': 284.0}, 'desire': {'precision': 0.6206896551724138, 'recall': 0.43373493975903615, 'f1-score': 0.5106382978723404, 'support': 83.0}, 'disappointment': {'precision': 0.3673469387755102, 'recall': 0.23841059602649006, 'f1-score': 0.2891566265060241, 'support': 151.0}, 'disapproval': {'precision': 0.4388185654008439, 'recall': 0.3895131086142322, 'f1-score': 0.4126984126984127, 'support': 267.0}, 'disgust': {'precision': 0.6410256410256411, 'recall': 0.4065040650406504, 'f1-score': 0.4975124378109453, 'support': 123.0}, 'embarrassment': {'precision': 0.7777777777777778, 'recall': 0.3783783783783784, 'f1-score': 0.509090909090909, 'support': 37.0}, 'excitement': {'precision': 0.4177215189873418, 'recall': 0.32038834951456313, 'f1-score': 0.3626373626373626, 'support': 103.0}, 'fear': {'precision': 0.5977011494252874, 'recall': 0.6666666666666666, 'f1-score': 0.6303030303030303, 'support': 78.0}, 'gratitude': {'precision': 0.9382352941176471, 'recall': 0.90625, 'f1-score': 0.9219653179190751, 'support': 352.0}, 'grief': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 6.0}, 'joy': {'precision': 0.6558441558441559, 'recall': 0.6273291925465838, 'f1-score': 0.6412698412698413, 'support': 161.0}, 'love': {'precision': 0.7763713080168776, 'recall': 0.773109243697479, 'f1-score': 0.7747368421052632, 'support': 238.0}, 'nervousness': {'precision': 0.3333333333333333, 'recall': 0.2608695652173913, 'f1-score': 0.2926829268292683, 'support': 23.0}, 'optimism': {'precision': 0.6716417910447762, 'recall': 0.4838709677419355, 'f1-score': 0.5625, 'support': 186.0}, 'pride': {'precision': 0.6666666666666666, 'recall': 0.125, 'f1-score': 0.21052631578947367, 'support': 16.0}, 'realization': {'precision': 0.3220338983050847, 'recall': 0.1310344827586207, 'f1-score': 0.18627450980392157, 'support': 145.0}, 'relief': {'precision': 0.5, 'recall': 0.09090909090909091, 'f1-score': 0.15384615384615385, 'support': 11.0}, 'remorse': {'precision': 0.5849056603773585, 'recall': 0.5535714285714286, 'f1-score': 0.5688073394495413, 'support': 56.0}, 'sadness': {'precision': 0.5909090909090909, 'recall': 0.5, 'f1-score': 0.5416666666666666, 'support': 156.0}, 'surprise': {'precision': 0.5113636363636364, 'recall': 0.6382978723404256, 'f1-score': 0.5678233438485805, 'support': 141.0}, 'neutral': {'precision': 0.6694915254237288, 'recall': 0.6189143816452154, 'f1-score': 0.6432102355335854, 'support': 1787.0}, 'micro avg': {'precision': 0.6252245777937477, 'recall': 0.5498498972981514, 'f1-score': 0.5851197982345523, 'support': 6329.0}, 'macro avg': {'precision': 0.5584146968787934, 'recall': 0.4443044578607666, 'f1-score': 0.4783253683909286, 'support': 6329.0}, 'weighted avg': {'precision': 0.6159179228918013, 'recall': 0.5498498972981514, 'f1-score': 0.5753626997680155, 'support': 6329.0}, 'samples avg': {'precision': 0.5807689945335053, 'recall': 0.5735366377986609, 'f1-score': 0.5644800687918433, 'support': 6329.0}}
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use 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: 45
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Exact Match Accuracy | Precision Micro | Recall Micro | F1 Micro | Precision Macro | Recall Macro | F1 Macro | Classification Report                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
+|:-------------:|:-----:|:-----:|:---------------:|:--------------------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| 0.1126        | 1.0   | 2714  | 0.0855          | 0.4565               | 0.6757          | 0.5042       | 0.5775   | 0.5644          | 0.3817       | 0.4259   | {'admiration': {'precision': 0.7566371681415929, 'recall': 0.7008196721311475, 'f1-score': 0.7276595744680852, 'support': 488.0}, 'amusement': {'precision': 0.7421203438395415, 'recall': 0.8547854785478548, 'f1-score': 0.7944785276073619, 'support': 303.0}, 'anger': {'precision': 0.6236559139784946, 'recall': 0.29743589743589743, 'f1-score': 0.4027777777777778, 'support': 195.0}, 'annoyance': {'precision': 0.4722222222222222, 'recall': 0.11221122112211221, 'f1-score': 0.18133333333333335, 'support': 303.0}, 'approval': {'precision': 0.5193370165745856, 'recall': 0.2367758186397985, 'f1-score': 0.32525951557093424, 'support': 397.0}, 'caring': {'precision': 0.5038167938931297, 'recall': 0.43137254901960786, 'f1-score': 0.4647887323943662, 'support': 153.0}, 'confusion': {'precision': 0.6363636363636364, 'recall': 0.27631578947368424, 'f1-score': 0.3853211009174312, 'support': 152.0}, 'curiosity': {'precision': 0.48109965635738833, 'recall': 0.5645161290322581, 'f1-score': 0.5194805194805194, 'support': 248.0}, 'desire': {'precision': 0.5862068965517241, 'recall': 0.44155844155844154, 'f1-score': 0.5037037037037037, 'support': 77.0}, 'disappointment': {'precision': 0.8, 'recall': 0.024539877300613498, 'f1-score': 0.047619047619047616, 'support': 163.0}, 'disapproval': {'precision': 0.5703125, 'recall': 0.25, 'f1-score': 0.3476190476190476, 'support': 292.0}, 'disgust': {'precision': 0.5102040816326531, 'recall': 0.25773195876288657, 'f1-score': 0.3424657534246575, 'support': 97.0}, 'embarrassment': {'precision': 0.9411764705882353, 'recall': 0.45714285714285713, 'f1-score': 0.6153846153846154, 'support': 35.0}, 'excitement': {'precision': 0.64, 'recall': 0.16666666666666666, 'f1-score': 0.2644628099173554, 'support': 96.0}, 'fear': {'precision': 0.8367346938775511, 'recall': 0.45555555555555555, 'f1-score': 0.5899280575539568, 'support': 90.0}, 'gratitude': {'precision': 0.9401197604790419, 'recall': 0.8770949720670391, 'f1-score': 0.9075144508670521, 'support': 358.0}, 'grief': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 13.0}, 'joy': {'precision': 0.5759493670886076, 'recall': 0.5290697674418605, 'f1-score': 0.5515151515151515, 'support': 172.0}, 'love': {'precision': 0.7231833910034602, 'recall': 0.8293650793650794, 'f1-score': 0.7726432532347505, 'support': 252.0}, 'nervousness': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 21.0}, 'optimism': {'precision': 0.7215189873417721, 'recall': 0.5454545454545454, 'f1-score': 0.6212534059945504, 'support': 209.0}, 'pride': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 15.0}, 'realization': {'precision': 0.84, 'recall': 0.16535433070866143, 'f1-score': 0.27631578947368424, 'support': 127.0}, 'relief': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 18.0}, 'remorse': {'precision': 0.65, 'recall': 0.5735294117647058, 'f1-score': 0.609375, 'support': 68.0}, 'sadness': {'precision': 0.5409836065573771, 'recall': 0.46153846153846156, 'f1-score': 0.4981132075471698, 'support': 143.0}, 'surprise': {'precision': 0.4935064935064935, 'recall': 0.5891472868217055, 'f1-score': 0.5371024734982333, 'support': 129.0}, 'neutral': {'precision': 0.6976588628762542, 'recall': 0.5906002265005662, 'f1-score': 0.6396810794234897, 'support': 1766.0}, 'micro avg': {'precision': 0.6756983826927117, 'recall': 0.5042319749216301, 'f1-score': 0.5775065074948389, 'support': 6380.0}, 'macro avg': {'precision': 0.5643859951026344, 'recall': 0.38173507121614314, 'f1-score': 0.4259212831545099, 'support': 6380.0}, 'weighted avg': {'precision': 0.6601848057578757, 'recall': 0.5042319749216301, 'f1-score': 0.5469066300328769, 'support': 6380.0}, 'samples avg': {'precision': 0.5558115247573412, 'recall': 0.531161690625384, 'f1-score': 0.5336712126796903, 'support': 6380.0}}                                                                                                                                                                                   |
+| 0.0782        | 2.0   | 5428  | 0.0879          | 0.4548               | 0.6364          | 0.5237       | 0.5745   | 0.5350          | 0.4147       | 0.4515   | {'admiration': {'precision': 0.6186708860759493, 'recall': 0.8012295081967213, 'f1-score': 0.6982142857142857, 'support': 488.0}, 'amusement': {'precision': 0.7597402597402597, 'recall': 0.7722772277227723, 'f1-score': 0.7659574468085106, 'support': 303.0}, 'anger': {'precision': 0.49504950495049505, 'recall': 0.5128205128205128, 'f1-score': 0.5037783375314862, 'support': 195.0}, 'annoyance': {'precision': 0.4666666666666667, 'recall': 0.25412541254125415, 'f1-score': 0.32905982905982906, 'support': 303.0}, 'approval': {'precision': 0.4605263157894737, 'recall': 0.26448362720403024, 'f1-score': 0.336, 'support': 397.0}, 'caring': {'precision': 0.5535714285714286, 'recall': 0.40522875816993464, 'f1-score': 0.4679245283018868, 'support': 153.0}, 'confusion': {'precision': 0.5, 'recall': 0.3815789473684211, 'f1-score': 0.43283582089552236, 'support': 152.0}, 'curiosity': {'precision': 0.5240384615384616, 'recall': 0.43951612903225806, 'f1-score': 0.4780701754385965, 'support': 248.0}, 'desire': {'precision': 0.6333333333333333, 'recall': 0.4935064935064935, 'f1-score': 0.5547445255474452, 'support': 77.0}, 'disappointment': {'precision': 0.410958904109589, 'recall': 0.18404907975460122, 'f1-score': 0.2542372881355932, 'support': 163.0}, 'disapproval': {'precision': 0.4948453608247423, 'recall': 0.3287671232876712, 'f1-score': 0.3950617283950617, 'support': 292.0}, 'disgust': {'precision': 0.4457831325301205, 'recall': 0.38144329896907214, 'f1-score': 0.4111111111111111, 'support': 97.0}, 'embarrassment': {'precision': 0.8, 'recall': 0.45714285714285713, 'f1-score': 0.5818181818181818, 'support': 35.0}, 'excitement': {'precision': 0.45454545454545453, 'recall': 0.3125, 'f1-score': 0.37037037037037035, 'support': 96.0}, 'fear': {'precision': 0.7121212121212122, 'recall': 0.5222222222222223, 'f1-score': 0.6025641025641025, 'support': 90.0}, 'gratitude': {'precision': 0.9437869822485208, 'recall': 0.8910614525139665, 'f1-score': 0.9166666666666666, 'support': 358.0}, 'grief': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 13.0}, 'joy': {'precision': 0.5621301775147929, 'recall': 0.5523255813953488, 'f1-score': 0.5571847507331378, 'support': 172.0}, 'love': {'precision': 0.7413793103448276, 'recall': 0.8531746031746031, 'f1-score': 0.7933579335793358, 'support': 252.0}, 'nervousness': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 21.0}, 'optimism': {'precision': 0.6981132075471698, 'recall': 0.5311004784688995, 'f1-score': 0.6032608695652174, 'support': 209.0}, 'pride': {'precision': 0.75, 'recall': 0.2, 'f1-score': 0.3157894736842105, 'support': 15.0}, 'realization': {'precision': 0.5789473684210527, 'recall': 0.1732283464566929, 'f1-score': 0.26666666666666666, 'support': 127.0}, 'relief': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 18.0}, 'remorse': {'precision': 0.6363636363636364, 'recall': 0.20588235294117646, 'f1-score': 0.3111111111111111, 'support': 68.0}, 'sadness': {'precision': 0.4607329842931937, 'recall': 0.6153846153846154, 'f1-score': 0.5269461077844312, 'support': 143.0}, 'surprise': {'precision': 0.576271186440678, 'recall': 0.5271317829457365, 'f1-score': 0.5506072874493927, 'support': 129.0}, 'neutral': {'precision': 0.7031700288184438, 'recall': 0.5526613816534541, 'f1-score': 0.6188966391883323, 'support': 1766.0}, 'micro avg': {'precision': 0.6363809523809524, 'recall': 0.523667711598746, 'f1-score': 0.574548581255374, 'support': 6380.0}, 'macro avg': {'precision': 0.5350266358139107, 'recall': 0.4147443497454755, 'f1-score': 0.45150840136144593, 'support': 6380.0}, 'weighted avg': {'precision': 0.6207079623001979, 'recall': 0.523667711598746, 'f1-score': 0.5577988370571888, 'support': 6380.0}, 'samples avg': {'precision': 0.5685895073104804, 'recall': 0.5473184666420936, 'f1-score': 0.546484299580503, 'support': 6380.0}}                                                                                                                                          |
+| 0.0657        | 3.0   | 8142  | 0.0904          | 0.4642               | 0.6287          | 0.5544       | 0.5892   | 0.5876          | 0.4548       | 0.4924   | {'admiration': {'precision': 0.7203389830508474, 'recall': 0.6967213114754098, 'f1-score': 0.7083333333333334, 'support': 488.0}, 'amusement': {'precision': 0.7391304347826086, 'recall': 0.8415841584158416, 'f1-score': 0.7870370370370371, 'support': 303.0}, 'anger': {'precision': 0.53125, 'recall': 0.5230769230769231, 'f1-score': 0.5271317829457365, 'support': 195.0}, 'annoyance': {'precision': 0.416988416988417, 'recall': 0.3564356435643564, 'f1-score': 0.38434163701067614, 'support': 303.0}, 'approval': {'precision': 0.4690265486725664, 'recall': 0.26700251889168763, 'f1-score': 0.3402889245585875, 'support': 397.0}, 'caring': {'precision': 0.6129032258064516, 'recall': 0.37254901960784315, 'f1-score': 0.4634146341463415, 'support': 153.0}, 'confusion': {'precision': 0.6086956521739131, 'recall': 0.3684210526315789, 'f1-score': 0.45901639344262296, 'support': 152.0}, 'curiosity': {'precision': 0.46206896551724136, 'recall': 0.5403225806451613, 'f1-score': 0.49814126394052044, 'support': 248.0}, 'desire': {'precision': 0.6190476190476191, 'recall': 0.5064935064935064, 'f1-score': 0.5571428571428572, 'support': 77.0}, 'disappointment': {'precision': 0.43137254901960786, 'recall': 0.26993865030674846, 'f1-score': 0.3320754716981132, 'support': 163.0}, 'disapproval': {'precision': 0.45064377682403434, 'recall': 0.3595890410958904, 'f1-score': 0.4, 'support': 292.0}, 'disgust': {'precision': 0.5405405405405406, 'recall': 0.41237113402061853, 'f1-score': 0.4678362573099415, 'support': 97.0}, 'embarrassment': {'precision': 0.6923076923076923, 'recall': 0.5142857142857142, 'f1-score': 0.5901639344262295, 'support': 35.0}, 'excitement': {'precision': 0.42857142857142855, 'recall': 0.3125, 'f1-score': 0.3614457831325301, 'support': 96.0}, 'fear': {'precision': 0.6857142857142857, 'recall': 0.5333333333333333, 'f1-score': 0.6, 'support': 90.0}, 'gratitude': {'precision': 0.9300291545189504, 'recall': 0.8910614525139665, 'f1-score': 0.9101283880171184, 'support': 358.0}, 'grief': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 13.0}, 'joy': {'precision': 0.5695364238410596, 'recall': 0.5, 'f1-score': 0.5325077399380805, 'support': 172.0}, 'love': {'precision': 0.7674418604651163, 'recall': 0.7857142857142857, 'f1-score': 0.7764705882352941, 'support': 252.0}, 'nervousness': {'precision': 0.4166666666666667, 'recall': 0.23809523809523808, 'f1-score': 0.30303030303030304, 'support': 21.0}, 'optimism': {'precision': 0.6792452830188679, 'recall': 0.5167464114832536, 'f1-score': 0.5869565217391305, 'support': 209.0}, 'pride': {'precision': 0.8333333333333334, 'recall': 0.3333333333333333, 'f1-score': 0.47619047619047616, 'support': 15.0}, 'realization': {'precision': 0.42857142857142855, 'recall': 0.2125984251968504, 'f1-score': 0.28421052631578947, 'support': 127.0}, 'relief': {'precision': 1.0, 'recall': 0.05555555555555555, 'f1-score': 0.10526315789473684, 'support': 18.0}, 'remorse': {'precision': 0.7391304347826086, 'recall': 0.5, 'f1-score': 0.5964912280701754, 'support': 68.0}, 'sadness': {'precision': 0.5314685314685315, 'recall': 0.5314685314685315, 'f1-score': 0.5314685314685315, 'support': 143.0}, 'surprise': {'precision': 0.48044692737430167, 'recall': 0.6666666666666666, 'f1-score': 0.5584415584415584, 'support': 129.0}, 'neutral': {'precision': 0.669481302774427, 'recall': 0.6285390713476784, 'f1-score': 0.6483644859813084, 'support': 1766.0}, 'micro avg': {'precision': 0.6286882332029862, 'recall': 0.5543887147335423, 'f1-score': 0.5892053973013494, 'support': 6380.0}, 'macro avg': {'precision': 0.5876411237797338, 'recall': 0.454800127114999, 'f1-score': 0.49235331483739386, 'support': 6380.0}, 'weighted avg': {'precision': 0.6194504501264384, 'recall': 0.5543887147335423, 'f1-score': 0.5787029045585259, 'support': 6380.0}, 'samples avg': {'precision': 0.5884629561371176, 'recall': 0.5802309866076913, 'f1-score': 0.5711635336036368, 'support': 6380.0}}                                                      |
+| 0.0537        | 4.0   | 10856 | 0.1009          | 0.4596               | 0.6020          | 0.5602       | 0.5803   | 0.5355          | 0.4616       | 0.4835   | {'admiration': {'precision': 0.6678260869565218, 'recall': 0.7868852459016393, 'f1-score': 0.7224835371589841, 'support': 488.0}, 'amusement': {'precision': 0.7100271002710027, 'recall': 0.8646864686468647, 'f1-score': 0.7797619047619048, 'support': 303.0}, 'anger': {'precision': 0.6551724137931034, 'recall': 0.38974358974358975, 'f1-score': 0.4887459807073955, 'support': 195.0}, 'annoyance': {'precision': 0.4825174825174825, 'recall': 0.22772277227722773, 'f1-score': 0.3094170403587444, 'support': 303.0}, 'approval': {'precision': 0.36342592592592593, 'recall': 0.3954659949622166, 'f1-score': 0.37876960193003617, 'support': 397.0}, 'caring': {'precision': 0.5470085470085471, 'recall': 0.41830065359477125, 'f1-score': 0.4740740740740741, 'support': 153.0}, 'confusion': {'precision': 0.37158469945355194, 'recall': 0.4473684210526316, 'f1-score': 0.4059701492537313, 'support': 152.0}, 'curiosity': {'precision': 0.47577092511013214, 'recall': 0.43548387096774194, 'f1-score': 0.45473684210526316, 'support': 248.0}, 'desire': {'precision': 0.5588235294117647, 'recall': 0.4935064935064935, 'f1-score': 0.5241379310344828, 'support': 77.0}, 'disappointment': {'precision': 0.37037037037037035, 'recall': 0.24539877300613497, 'f1-score': 0.2952029520295203, 'support': 163.0}, 'disapproval': {'precision': 0.4838709677419355, 'recall': 0.2568493150684932, 'f1-score': 0.33557046979865773, 'support': 292.0}, 'disgust': {'precision': 0.5, 'recall': 0.41237113402061853, 'f1-score': 0.4519774011299435, 'support': 97.0}, 'embarrassment': {'precision': 0.6785714285714286, 'recall': 0.5428571428571428, 'f1-score': 0.6031746031746031, 'support': 35.0}, 'excitement': {'precision': 0.46153846153846156, 'recall': 0.3125, 'f1-score': 0.37267080745341613, 'support': 96.0}, 'fear': {'precision': 0.7794117647058824, 'recall': 0.5888888888888889, 'f1-score': 0.6708860759493671, 'support': 90.0}, 'gratitude': {'precision': 0.9093484419263456, 'recall': 0.8966480446927374, 'f1-score': 0.9029535864978903, 'support': 358.0}, 'grief': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 13.0}, 'joy': {'precision': 0.5549132947976878, 'recall': 0.5581395348837209, 'f1-score': 0.5565217391304348, 'support': 172.0}, 'love': {'precision': 0.7285714285714285, 'recall': 0.8095238095238095, 'f1-score': 0.7669172932330827, 'support': 252.0}, 'nervousness': {'precision': 0.4, 'recall': 0.09523809523809523, 'f1-score': 0.15384615384615385, 'support': 21.0}, 'optimism': {'precision': 0.5821596244131455, 'recall': 0.5933014354066986, 'f1-score': 0.5876777251184834, 'support': 209.0}, 'pride': {'precision': 0.8571428571428571, 'recall': 0.4, 'f1-score': 0.5454545454545454, 'support': 15.0}, 'realization': {'precision': 0.2076923076923077, 'recall': 0.2125984251968504, 'f1-score': 0.21011673151750973, 'support': 127.0}, 'relief': {'precision': 0.2, 'recall': 0.05555555555555555, 'f1-score': 0.08695652173913043, 'support': 18.0}, 'remorse': {'precision': 0.6790123456790124, 'recall': 0.8088235294117647, 'f1-score': 0.738255033557047, 'support': 68.0}, 'sadness': {'precision': 0.5546875, 'recall': 0.4965034965034965, 'f1-score': 0.5239852398523985, 'support': 143.0}, 'surprise': {'precision': 0.5590551181102362, 'recall': 0.5503875968992248, 'f1-score': 0.5546875, 'support': 129.0}, 'neutral': {'precision': 0.654320987654321, 'recall': 0.630237825594564, 'f1-score': 0.6420536486876262, 'support': 1766.0}, 'micro avg': {'precision': 0.6019875357924878, 'recall': 0.5601880877742946, 'f1-score': 0.5803361208086385, 'support': 6380.0}, 'macro avg': {'precision': 0.5354579860486948, 'recall': 0.4616066469071776, 'f1-score': 0.4834644674840867, 'support': 6380.0}, 'weighted avg': {'precision': 0.592394586579407, 'recall': 0.5601880877742946, 'f1-score': 0.5686740247500924, 'support': 6380.0}, 'samples avg': {'precision': 0.5820125322521195, 'recall': 0.5823196952942622, 'f1-score': 0.5690054938304109, 'support': 6380.0}}                                               |
+| 0.0434        | 5.0   | 13570 | 0.1089          | 0.4228               | 0.5765          | 0.5373       | 0.5562   | 0.5047          | 0.4658       | 0.4732   | {'admiration': {'precision': 0.6920077972709552, 'recall': 0.7274590163934426, 'f1-score': 0.7092907092907093, 'support': 488.0}, 'amusement': {'precision': 0.745398773006135, 'recall': 0.801980198019802, 'f1-score': 0.7726550079491256, 'support': 303.0}, 'anger': {'precision': 0.47549019607843135, 'recall': 0.49743589743589745, 'f1-score': 0.48621553884711777, 'support': 195.0}, 'annoyance': {'precision': 0.3623693379790941, 'recall': 0.3432343234323432, 'f1-score': 0.3525423728813559, 'support': 303.0}, 'approval': {'precision': 0.37388724035608306, 'recall': 0.31738035264483627, 'f1-score': 0.34332425068119893, 'support': 397.0}, 'caring': {'precision': 0.48872180451127817, 'recall': 0.42483660130718953, 'f1-score': 0.45454545454545453, 'support': 153.0}, 'confusion': {'precision': 0.463768115942029, 'recall': 0.42105263157894735, 'f1-score': 0.4413793103448276, 'support': 152.0}, 'curiosity': {'precision': 0.4386503067484663, 'recall': 0.5766129032258065, 'f1-score': 0.49825783972125437, 'support': 248.0}, 'desire': {'precision': 0.5185185185185185, 'recall': 0.5454545454545454, 'f1-score': 0.5316455696202531, 'support': 77.0}, 'disappointment': {'precision': 0.32456140350877194, 'recall': 0.22699386503067484, 'f1-score': 0.26714801444043323, 'support': 163.0}, 'disapproval': {'precision': 0.38028169014084506, 'recall': 0.3698630136986301, 'f1-score': 0.375, 'support': 292.0}, 'disgust': {'precision': 0.4434782608695652, 'recall': 0.5257731958762887, 'f1-score': 0.4811320754716981, 'support': 97.0}, 'embarrassment': {'precision': 0.6333333333333333, 'recall': 0.5428571428571428, 'f1-score': 0.5846153846153846, 'support': 35.0}, 'excitement': {'precision': 0.35294117647058826, 'recall': 0.375, 'f1-score': 0.36363636363636365, 'support': 96.0}, 'fear': {'precision': 0.7083333333333334, 'recall': 0.5666666666666667, 'f1-score': 0.6296296296296297, 'support': 90.0}, 'gratitude': {'precision': 0.9300291545189504, 'recall': 0.8910614525139665, 'f1-score': 0.9101283880171184, 'support': 358.0}, 'grief': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 13.0}, 'joy': {'precision': 0.5448717948717948, 'recall': 0.4941860465116279, 'f1-score': 0.5182926829268293, 'support': 172.0}, 'love': {'precision': 0.67601246105919, 'recall': 0.8611111111111112, 'f1-score': 0.7574171029668412, 'support': 252.0}, 'nervousness': {'precision': 0.4, 'recall': 0.09523809523809523, 'f1-score': 0.15384615384615385, 'support': 21.0}, 'optimism': {'precision': 0.5435684647302904, 'recall': 0.6267942583732058, 'f1-score': 0.5822222222222222, 'support': 209.0}, 'pride': {'precision': 0.75, 'recall': 0.2, 'f1-score': 0.3157894736842105, 'support': 15.0}, 'realization': {'precision': 0.19424460431654678, 'recall': 0.2125984251968504, 'f1-score': 0.20300751879699247, 'support': 127.0}, 'relief': {'precision': 0.18181818181818182, 'recall': 0.1111111111111111, 'f1-score': 0.13793103448275862, 'support': 18.0}, 'remorse': {'precision': 0.7361111111111112, 'recall': 0.7794117647058824, 'f1-score': 0.7571428571428571, 'support': 68.0}, 'sadness': {'precision': 0.5068493150684932, 'recall': 0.5174825174825175, 'f1-score': 0.5121107266435986, 'support': 143.0}, 'surprise': {'precision': 0.5865384615384616, 'recall': 0.4728682170542636, 'f1-score': 0.5236051502145923, 'support': 129.0}, 'neutral': {'precision': 0.680327868852459, 'recall': 0.5169875424688561, 'f1-score': 0.5875160875160875, 'support': 1766.0}, 'micro avg': {'precision': 0.5765220316178944, 'recall': 0.5373040752351097, 'f1-score': 0.556222618854454, 'support': 6380.0}, 'macro avg': {'precision': 0.5047183109268895, 'recall': 0.46576610340677504, 'f1-score': 0.47321524714768104, 'support': 6380.0}, 'weighted avg': {'precision': 0.5788599597470344, 'recall': 0.5373040752351097, 'f1-score': 0.552452450376, 'support': 6380.0}, 'samples avg': {'precision': 0.5527091780316993, 'recall': 0.5559343899741983, 'f1-score': 0.5401874572165762, 'support': 6380.0}}                             |
+| 0.0349        | 6.0   | 16284 | 0.1183          | 0.4423               | 0.5841          | 0.5630       | 0.5733   | 0.5372          | 0.4850       | 0.4930   | {'admiration': {'precision': 0.6482982171799028, 'recall': 0.819672131147541, 'f1-score': 0.7239819004524887, 'support': 488.0}, 'amusement': {'precision': 0.7386363636363636, 'recall': 0.858085808580858, 'f1-score': 0.7938931297709924, 'support': 303.0}, 'anger': {'precision': 0.5, 'recall': 0.5025641025641026, 'f1-score': 0.5012787723785166, 'support': 195.0}, 'annoyance': {'precision': 0.40969162995594716, 'recall': 0.3069306930693069, 'f1-score': 0.35094339622641507, 'support': 303.0}, 'approval': {'precision': 0.3697916666666667, 'recall': 0.35768261964735515, 'f1-score': 0.36363636363636365, 'support': 397.0}, 'caring': {'precision': 0.5109489051094891, 'recall': 0.45751633986928103, 'f1-score': 0.4827586206896552, 'support': 153.0}, 'confusion': {'precision': 0.4676258992805755, 'recall': 0.4276315789473684, 'f1-score': 0.44673539518900346, 'support': 152.0}, 'curiosity': {'precision': 0.48188405797101447, 'recall': 0.5362903225806451, 'f1-score': 0.5076335877862596, 'support': 248.0}, 'desire': {'precision': 0.4270833333333333, 'recall': 0.5324675324675324, 'f1-score': 0.47398843930635837, 'support': 77.0}, 'disappointment': {'precision': 0.336283185840708, 'recall': 0.2331288343558282, 'f1-score': 0.2753623188405797, 'support': 163.0}, 'disapproval': {'precision': 0.3665594855305466, 'recall': 0.3904109589041096, 'f1-score': 0.3781094527363184, 'support': 292.0}, 'disgust': {'precision': 0.5, 'recall': 0.4020618556701031, 'f1-score': 0.44571428571428573, 'support': 97.0}, 'embarrassment': {'precision': 0.59375, 'recall': 0.5428571428571428, 'f1-score': 0.5671641791044776, 'support': 35.0}, 'excitement': {'precision': 0.3305785123966942, 'recall': 0.4166666666666667, 'f1-score': 0.3686635944700461, 'support': 96.0}, 'fear': {'precision': 0.7058823529411765, 'recall': 0.5333333333333333, 'f1-score': 0.6075949367088608, 'support': 90.0}, 'gratitude': {'precision': 0.9169054441260746, 'recall': 0.8938547486033519, 'f1-score': 0.9052333804809052, 'support': 358.0}, 'grief': {'precision': 1.0, 'recall': 0.15384615384615385, 'f1-score': 0.26666666666666666, 'support': 13.0}, 'joy': {'precision': 0.5735294117647058, 'recall': 0.45348837209302323, 'f1-score': 0.5064935064935064, 'support': 172.0}, 'love': {'precision': 0.7420494699646644, 'recall': 0.8333333333333334, 'f1-score': 0.7850467289719626, 'support': 252.0}, 'nervousness': {'precision': 0.3333333333333333, 'recall': 0.14285714285714285, 'f1-score': 0.2, 'support': 21.0}, 'optimism': {'precision': 0.585, 'recall': 0.5598086124401914, 'f1-score': 0.5721271393643031, 'support': 209.0}, 'pride': {'precision': 0.7142857142857143, 'recall': 0.3333333333333333, 'f1-score': 0.45454545454545453, 'support': 15.0}, 'realization': {'precision': 0.25225225225225223, 'recall': 0.2204724409448819, 'f1-score': 0.23529411764705882, 'support': 127.0}, 'relief': {'precision': 0.13333333333333333, 'recall': 0.1111111111111111, 'f1-score': 0.12121212121212122, 'support': 18.0}, 'remorse': {'precision': 0.6867469879518072, 'recall': 0.8382352941176471, 'f1-score': 0.7549668874172185, 'support': 68.0}, 'sadness': {'precision': 0.5298013245033113, 'recall': 0.5594405594405595, 'f1-score': 0.54421768707483, 'support': 143.0}, 'surprise': {'precision': 0.5170068027210885, 'recall': 0.5891472868217055, 'f1-score': 0.5507246376811594, 'support': 129.0}, 'neutral': {'precision': 0.671523178807947, 'recall': 0.5741789354473387, 'f1-score': 0.6190476190476191, 'support': 1766.0}, 'micro avg': {'precision': 0.5840650406504065, 'recall': 0.5630094043887147, 'f1-score': 0.5733439744612929, 'support': 6380.0}, 'macro avg': {'precision': 0.5372421736745232, 'recall': 0.48501454446610526, 'f1-score': 0.49296551141476525, 'support': 6380.0}, 'weighted avg': {'precision': 0.5819808943352951, 'recall': 0.5630094043887147, 'f1-score': 0.5679464375851392, 'support': 6380.0}, 'samples avg': {'precision': 0.5731048040299792, 'recall': 0.58474628332719, 'f1-score': 0.564147929721096, 'support': 6380.0}} |
+
+
+### Framework versions
+
+- Transformers 4.50.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.21.1

config.json

@@ -0,0 +1,93 @@
+{
+  "architectures": [
+    "DebertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6",
+    "7": "LABEL_7",
+    "8": "LABEL_8",
+    "9": "LABEL_9",
+    "10": "LABEL_10",
+    "11": "LABEL_11",
+    "12": "LABEL_12",
+    "13": "LABEL_13",
+    "14": "LABEL_14",
+    "15": "LABEL_15",
+    "16": "LABEL_16",
+    "17": "LABEL_17",
+    "18": "LABEL_18",
+    "19": "LABEL_19",
+    "20": "LABEL_20",
+    "21": "LABEL_21",
+    "22": "LABEL_22",
+    "23": "LABEL_23",
+    "24": "LABEL_24",
+    "25": "LABEL_25",
+    "26": "LABEL_26",
+    "27": "LABEL_27"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_10": 10,
+    "LABEL_11": 11,
+    "LABEL_12": 12,
+    "LABEL_13": 13,
+    "LABEL_14": 14,
+    "LABEL_15": 15,
+    "LABEL_16": 16,
+    "LABEL_17": 17,
+    "LABEL_18": 18,
+    "LABEL_19": 19,
+    "LABEL_2": 2,
+    "LABEL_20": 20,
+    "LABEL_21": 21,
+    "LABEL_22": 22,
+    "LABEL_23": 23,
+    "LABEL_24": 24,
+    "LABEL_25": 25,
+    "LABEL_26": 26,
+    "LABEL_27": 27,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6,
+    "LABEL_7": 7,
+    "LABEL_8": 8,
+    "LABEL_9": 9
+  },
+  "layer_norm_eps": 1e-07,
+  "legacy": true,
+  "max_position_embeddings": 512,
+  "max_relative_positions": -1,
+  "model_type": "deberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "pooler_dropout": 0,
+  "pooler_hidden_act": "gelu",
+  "pooler_hidden_size": 768,
+  "pos_att_type": [
+    "c2p",
+    "p2c"
+  ],
+  "position_biased_input": false,
+  "problem_type": "multi_label_classification",
+  "relative_attention": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.50.3",
+  "type_vocab_size": 0,
+  "vocab_size": 50265
+}

metrics/summary.txt

@@ -0,0 +1,17 @@
+Model: microsoft/deberta-base
+Training completed on: 2025-04-06 00:27:38
+Results directory: ./results/20250406_000832
+TensorBoard logs: tensorboard --logdir=./results/20250406_000832
+View results with: python mode.py --hub_model_id suku9/emotion_classifier --view_results ./results/20250406_000832
+
+=== Train Results ===
+Micro F1: 0.7785
+Macro F1: 0.6870
+
+=== Validation Results ===
+Micro F1: 0.5892
+Macro F1: 0.4924
+
+=== Test Results ===
+Micro F1: 0.5851
+Macro F1: 0.4783

metrics/test_results.json

@@ -0,0 +1,209 @@
+{
+  "eval_loss": 0.09008365124464035,
+  "eval_exact_match_accuracy": 0.4615809839690437,
+  "eval_precision_micro": 0.6252245777937477,
+  "eval_recall_micro": 0.5498498972981514,
+  "eval_f1_micro": 0.5851197982345523,
+  "eval_precision_macro": 0.5584146968787934,
+  "eval_recall_macro": 0.4443044578607666,
+  "eval_f1_macro": 0.4783253683909286,
+  "eval_classification_report": {
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+  "eos_token": "[SEP]",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "tokenizer_class": "DebertaTokenizer",
+  "unk_token": "[UNK]",
+  "vocab_type": "gpt2"
+}

training_args.bin

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