ankitb10/question_classification_model

1---2license: apache-2.03base_model: distilbert/distilbert-base-uncased4tags:5- generated_from_trainer6metrics:7- accuracy8model-index:9- name: everyview_question_classification_model10  results: []11---12 13<!-- This model card has been generated automatically according to the information the Trainer had access to. You14should probably proofread and complete it, then remove this comment. -->15 16# question_classification_model17 18This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.19It achieves the following results on the evaluation set:20- Loss: 0.014121- Accuracy: 1.022 23## Model description24 25More information needed26 27## Intended uses & limitations28 29More information needed30 31## Training and evaluation data32 33More information needed34 35## Training procedure36 37### Training hyperparameters38 39The following hyperparameters were used during training:40- learning_rate: 2e-0541- train_batch_size: 242- eval_batch_size: 243- seed: 4244- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0845- lr_scheduler_type: linear46- num_epochs: 2047 48### Training results49 50| Training Loss | Epoch | Step | Validation Loss | Accuracy |51|:-------------:|:-----:|:----:|:---------------:|:--------:|52| 1.0644        | 0.5   | 5    | 1.1973          | 0.0      |53| 1.1768        | 1.0   | 10   | 1.1003          | 0.0      |54| 1.0388        | 1.5   | 15   | 0.9396          | 1.0      |55| 0.9709        | 2.0   | 20   | 0.8235          | 1.0      |56| 1.0193        | 2.5   | 25   | 0.7088          | 1.0      |57| 0.7945        | 3.0   | 30   | 0.5735          | 1.0      |58| 0.9431        | 3.5   | 35   | 0.4812          | 1.0      |59| 0.7091        | 4.0   | 40   | 0.4083          | 1.0      |60| 0.7901        | 4.5   | 45   | 0.3773          | 1.0      |61| 0.7049        | 5.0   | 50   | 0.2875          | 1.0      |62| 0.5757        | 5.5   | 55   | 0.2608          | 1.0      |63| 0.6503        | 6.0   | 60   | 0.2752          | 1.0      |64| 0.6157        | 6.5   | 65   | 0.2288          | 1.0      |65| 0.4012        | 7.0   | 70   | 0.1577          | 1.0      |66| 0.5781        | 7.5   | 75   | 0.1294          | 1.0      |67| 0.2576        | 8.0   | 80   | 0.1047          | 1.0      |68| 0.5107        | 8.5   | 85   | 0.0842          | 1.0      |69| 0.1516        | 9.0   | 90   | 0.0711          | 1.0      |70| 0.2649        | 9.5   | 95   | 0.0581          | 1.0      |71| 0.2855        | 10.0  | 100  | 0.0485          | 1.0      |72| 0.2232        | 10.5  | 105  | 0.0401          | 1.0      |73| 0.2213        | 11.0  | 110  | 0.0344          | 1.0      |74| 0.2809        | 11.5  | 115  | 0.0299          | 1.0      |75| 0.0889        | 12.0  | 120  | 0.0268          | 1.0      |76| 0.0933        | 12.5  | 125  | 0.0244          | 1.0      |77| 0.2543        | 13.0  | 130  | 0.0225          | 1.0      |78| 0.1446        | 13.5  | 135  | 0.0204          | 1.0      |79| 0.2565        | 14.0  | 140  | 0.0188          | 1.0      |80| 0.1347        | 14.5  | 145  | 0.0179          | 1.0      |81| 0.1464        | 15.0  | 150  | 0.0172          | 1.0      |82| 0.0365        | 15.5  | 155  | 0.0165          | 1.0      |83| 0.2711        | 16.0  | 160  | 0.0159          | 1.0      |84| 0.1889        | 16.5  | 165  | 0.0155          | 1.0      |85| 0.0336        | 17.0  | 170  | 0.0152          | 1.0      |86| 0.1712        | 17.5  | 175  | 0.0149          | 1.0      |87| 0.0366        | 18.0  | 180  | 0.0146          | 1.0      |88| 0.1819        | 18.5  | 185  | 0.0144          | 1.0      |89| 0.0353        | 19.0  | 190  | 0.0142          | 1.0      |90| 0.092         | 19.5  | 195  | 0.0142          | 1.0      |91| 0.0991        | 20.0  | 200  | 0.0141          | 1.0      |92 93 94### Framework versions95 96- Transformers 4.40.097- Pytorch 2.2.298- Datasets 2.19.199- Tokenizers 0.19.1100