Realgon/N_roberta_imdb_padding60model

1---2license: mit3base_model: roberta-base4tags:5- generated_from_trainer6datasets:7- imdb8metrics:9- accuracy10model-index:11- name: N_roberta_imdb_padding60model12  results:13  - task:14      name: Text Classification15      type: text-classification16    dataset:17      name: imdb18      type: imdb19      config: plain_text20      split: test21      args: plain_text22    metrics:23    - name: Accuracy24      type: accuracy25      value: 0.9500426---27 28<!-- This model card has been generated automatically according to the information the Trainer had access to. You29should probably proofread and complete it, then remove this comment. -->30 31# N_roberta_imdb_padding60model32 33This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the imdb dataset.34It achieves the following results on the evaluation set:35- Loss: 0.481136- Accuracy: 0.950037 38## Model description39 40More information needed41 42## Intended uses & limitations43 44More information needed45 46## Training and evaluation data47 48More information needed49 50## Training procedure51 52### Training hyperparameters53 54The following hyperparameters were used during training:55- learning_rate: 2e-0556- train_batch_size: 1657- eval_batch_size: 1658- seed: 4259- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0860- lr_scheduler_type: linear61- num_epochs: 2062 63### Training results64 65| Training Loss | Epoch | Step  | Validation Loss | Accuracy |66|:-------------:|:-----:|:-----:|:---------------:|:--------:|67| 0.2157        | 1.0   | 1563  | 0.2020          | 0.9366   |68| 0.1716        | 2.0   | 3126  | 0.1757          | 0.9467   |69| 0.1135        | 3.0   | 4689  | 0.2601          | 0.9442   |70| 0.0834        | 4.0   | 6252  | 0.2498          | 0.9485   |71| 0.0533        | 5.0   | 7815  | 0.3480          | 0.9452   |72| 0.0441        | 6.0   | 9378  | 0.3548          | 0.9371   |73| 0.0319        | 7.0   | 10941 | 0.3257          | 0.9474   |74| 0.0264        | 8.0   | 12504 | 0.3932          | 0.9457   |75| 0.0239        | 9.0   | 14067 | 0.3367          | 0.9469   |76| 0.0185        | 10.0  | 15630 | 0.4500          | 0.94     |77| 0.018         | 11.0  | 17193 | 0.3871          | 0.9470   |78| 0.0153        | 12.0  | 18756 | 0.4206          | 0.9456   |79| 0.0101        | 13.0  | 20319 | 0.4027          | 0.9492   |80| 0.005         | 14.0  | 21882 | 0.4701          | 0.9477   |81| 0.0051        | 15.0  | 23445 | 0.4454          | 0.9484   |82| 0.0013        | 16.0  | 25008 | 0.5015          | 0.9493   |83| 0.007         | 17.0  | 26571 | 0.5011          | 0.9476   |84| 0.0022        | 18.0  | 28134 | 0.4798          | 0.95     |85| 0.0047        | 19.0  | 29697 | 0.4794          | 0.9498   |86| 0.0014        | 20.0  | 31260 | 0.4811          | 0.9500   |87 88 89### Framework versions90 91- Transformers 4.33.292- Pytorch 2.0.1+cu11793- Datasets 2.14.594- Tokenizers 0.13.395